Pluralsight Path. Deep Learning Literacy. Practical Application (2022)

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Pluralsight Path. Deep Learning Literacy. Practical Application (2022)

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文件列表

  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/exercise.7z 73.1 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/2. Demo - Fine Tuning Glove and FastText.mp4 67.6 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/6. Demo - Training a CBOW Embedding.mp4 42.4 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/4. Demo - Debiase Word Embeddings.mp4 40.3 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/3. Demo - Using OHE.mp4 33.5 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/3. Demo - Bringing It into Practice.mp4 31.4 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/07. Demo - Exploratory Data Analysis and Data Cleaning.mp4 30.6 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/7. Demo - Reanalyze Sentiment with a Network-based Embedding.mp4 27.7 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/exercise.7z 27.3 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/2. Demo - Load and Explore the Dataset.mp4 26.3 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/4. Training a Model - Scripted and PaaS.mp4 24.4 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/09. Demo - Building a Model for Anomaly Detection.mp4 23.5 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/4. Demo - Analyzing Sentiment with OHE.mp4 23.5 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/5. Demo - User-based Collaborative Filtering.mp4 23.0 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/3. Demo - Pre-processing the Images Data.mp4 22.7 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/3. Demo - Making Word Clusters.mp4 21.4 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/6. Demo - Item-based Collaborative Filtering.mp4 21.2 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/4. Demo - Pre-processing the Captions Data.mp4 20.6 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/2. Drift, Retaining, and Model Store.mp4 20.1 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/08. Demo - Data Preprocessing and Dimensionality Reduction.mp4 19.2 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/4. Demo - Dataset Introduction and Exploratory Data Analysis.mp4 18.8 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/4. Demo - Book Recommendations with Deep Learning.mp4 18.5 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/06. Demo - Image Augmentation and Hyperparameter Tuning.mp4 18.0 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/3. Evaluation Metrics for Image Captioning.mp4 17.8 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/5. Functions to Preprocess the Dataset.mp4 16.4 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/2. Demo - Evaluating the Anomaly Detection Models.mp4 16.3 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/3. Exploring Data Driven Trends in Marketing.mp4 15.8 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/1. Deployment and MLOps.mp4 14.9 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/4. Understanding the Three Stages of Conversational Artificial Intelligence.mp4 14.3 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/3. Demo - Movie Recommendations with SVD.mp4 13.9 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/2. Understanding Model-based Collaborative Filtering.mp4 13.9 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/2. Implementation.mp4 13.9 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/exercise.7z 13.9 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/2. Demo - Build the Attention Model for Image-captioning Using TensorFlow.mp4 13.7 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/3. Tokenization, Vocabulary, and N-grams.mp4 13.5 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/1. Module and Project Overview.mp4 13.3 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/1. Detector Models, Frameworks, and Libraries.mp4 13.0 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/4. Clean the Email Dataset.mp4 12.5 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/4. Recurrent Neural Networks (RNNs).mp4 12.3 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/5. Demo - Prepare Training Data Using Pre-processed Data.mp4 12.2 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/exercise.7z 12.2 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/4. Demo - Organizing the Dataset.mp4 11.7 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/07. Demo - Creating the CNN Architecture.mp4 11.3 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/5. Long Short-term Memory Networks (LSTMs).mp4 11.1 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/6. Preprocess the Email Dataset.mp4 10.8 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/4. Demo - Input Data of Tesla Stock.mp4 10.8 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/6. Demo - Preprocessing and Preparing the Dataset.mp4 10.8 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/2. What Are We Trying to Solve.mp4 10.4 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/6. Demo - Perform Model Training.mp4 10.4 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/7. Generate Auto-complete Suggestions.mp4 10.3 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/2. Introduction to Neural Networks.mp4 10.2 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/2. Introduction to Healthcare Data.mp4 10.2 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/6. Build and Train the Model.mp4 10.2 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/4. Proposed Solutions for Image Captioning Case Study.mp4 10.1 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/5. Recommender Systems - Business Use Cases.mp4 10.0 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/3. What Is Deep Learning.mp4 9.7 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/5. Image Analysis.mp4 9.7 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/1. Building a Foundation.mp4 9.7 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/3. Results.mp4 9.5 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/6. Networks Architectures Using LSTMs.mp4 9.1 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/7. Case study - Automated Medical Coding.mp4 9.1 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/3. Extract Plaintext Messages from Raw Email Data.mp4 9.1 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/6. Case Study - Diagnostic Image Analysis.mp4 8.9 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/2. What Is Time Series Data.mp4 8.9 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/4. Handle Variable Sentence Lengths.mp4 8.7 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/6. Device Data.mp4 8.6 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/2. Network Architecture for Text Generation.mp4 8.5 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/1. Use Case - Customer Segmentation.mp4 8.5 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/7. Understanding Generative Adversarial Networks.mp4 8.4 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/5. Training Embeddings with Networks - CBOW and Skip-gram.mp4 8.3 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/6. Demo - Setting up Your Environment.mp4 8.0 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/04. CNN - Activation.mp4 8.0 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/exercise.7z 8.0 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/03. Procuring Additional Training Data - Image Augmentation.mp4 7.8 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/2. Building up Your Dataset.mp4 7.7 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/09. Demo - Improving Performance through Transfer Learning.mp4 7.6 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/3. Content-based Filtering.mp4 7.4 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/exercise.7z 7.2 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/2. Meshed Memory Transformer for Image Captioning.mp4 7.2 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/03. CNN - Convolutions.mp4 7.1 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/4. Demo - Implement RNN Decoder with Attention & Sentence Generator.mp4 7.1 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/4. Stationarity and Autocorrelation.mp4 7.1 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/5. Demo - Define the Loss Function and Model Checkpoints.mp4 7.1 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/09. Demo - Performance Metrics - How Well Did Your Model Do.mp4 7.0 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/exercise.7z 7.0 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/5. Peer Review.mp4 7.0 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/3. Analysing Time Series Data.mp4 7.0 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/07. What Is Transfer Learning.mp4 7.0 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/5. Demo - Exploring the Dataset.mp4 7.0 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/3. Demo - Setting up Your Environment.mp4 7.0 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/3. Demo - Setting up Your Environment.mp4 6.9 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/4. Document and Text Analysis.mp4 6.9 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/1. Overview.mp4 6.8 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/4. Demo - Training Stacked LSTM Model.mp4 6.8 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/3. Case Study - Recommendation Systems/1. Framing the Problem.mp4 6.8 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/03. Classification and Regression Trees (CART).mp4 6.8 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/5. Data Collection.mp4 6.7 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/5. Summary/1. Summary.mp4 6.6 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/3. General Object Detection Script Setup.mp4 6.6 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/2. Understanding Memory-based Collaborative Filtering.mp4 6.5 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/1. Discussing the Importance of Neural Network in Finance.mp4 6.3 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/3. Medical Coding.mp4 6.3 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/2. DataFormats and Computing.mp4 6.3 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/2. What Is Image Captioning and Why Is It Important.mp4 6.2 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/5. Predictors and Labels for Training.mp4 6.1 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/08. Transfer Learning – When and How.mp4 6.0 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/7. Natural Language Generation Using LSTMs.mp4 6.0 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/04. Clustering-based Anomaly Detection.mp4 5.9 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/5. Introduction to Anomaly Detection.mp4 5.9 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/2. Explore Enron Email Dataset.mp4 5.9 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/exercise.7z 5.8 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/6. Current Trends.mp4 5.8 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/4. Getting Started with Artificial Intelligence.mp4 5.8 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/05. Overfitting and Underfitting.mp4 5.7 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/8. Utilizing Generative Adversarial Networks in Personalized Interactions.mp4 5.6 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/1. Why Should We Process Text.mp4 5.6 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/5. Demo - Evaluate the Model to Predict Future Price of Tesla Stock.mp4 5.6 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/6. Case study - Sepsis Algorithm.mp4 5.5 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/2. Decision Support vs. Decision Making.mp4 5.5 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/2. Introducing Customer Engagement Marketing.mp4 5.5 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/1. Course and Module Introduction.mp4 5.5 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/2. Introducing Data Driven Marketing.mp4 5.4 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/06. Demo - Introduction to the Problem and Dataset.mp4 5.4 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/3. Natural Language Text as Sequential Data.mp4 5.4 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/6. Introducing Deep Learning.mp4 5.3 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/2. What Are Recommendation Systems.mp4 5.3 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/05. Anomaly Detection Using Autoencoders.mp4 5.2 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/2. Importance of Back Propagation.mp4 5.2 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/4. Bias.mp4 5.1 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/3. Case Study - Recommendation Systems/2. Implementation.mp4 5.1 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/2. Use Case - Inventory Management.mp4 5.1 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/3. Interpretability.mp4 5.1 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/1. How to Represent Words.mp4 5.0 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/3. Case Study - Recommendation Systems/3. Results.mp4 5.0 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/4. Use Case - Price Optimization.mp4 4.9 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/5. Getting Acquainted with Machine Learning.mp4 4.9 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/7. Demo - Making Predictions out of the Trained Model.mp4 4.7 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/04. Hyperparameter Tuning.mp4 4.6 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/08. Demo - Training the Model.mp4 4.6 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/4. Advantages.mp4 4.6 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/7. Understanding Deep Learning Applications in Marketing.mp4 4.6 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/5. Disadvantages.mp4 4.5 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/2. The Power of Deep Learning.mp4 4.4 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/5. Summary.mp4 4.4 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/1. Course Overview/1. Course Overview.mp4 4.3 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/4. Bottom-up and Top-down Attention for Image Captioning.mp4 4.3 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/3. Understanding CNN and RNN.mp4 4.3 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/6. Where to Go Next.mp4 4.2 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/3. Use Case - Product Image Classification.mp4 4.2 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/exercise.7z 4.2 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/02. What Are Convolutional Neural Networks.mp4 4.2 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/2. First Embedding - One Hot Encoding.mp4 4.1 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/1. Framing the Problem.mp4 4.0 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/3. Getting the Best out of This Course.mp4 4.0 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/6. Demo - Preparing Training and Test Dataset.mp4 3.9 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/1. Course and Module Summary.mp4 3.9 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/3. Demo - Implement CNN Encoder in TensorFlow.mp4 3.9 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/6. Introducing Personalized Customer Interactions.mp4 3.9 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/3. Explaining Conversational Artificial Intelligence.mp4 3.8 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/1. Why Would We Fine Tune Existing Models.mp4 3.8 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/1. Parameters Impacting the Stock Price of Tesla.mp4 3.8 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/exercise.7z 3.7 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/1. Course Overview/1. Course Overview.mp4 3.6 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/1. Challenges of RNN.mp4 3.6 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/4. Risks and Problems Associated with Finance Industry.mp4 3.6 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/4. Tips for Success.mp4 3.5 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/3. Introducing the Business Case Study for Image-captioning.mp4 3.5 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/1. Course Overview/1. Course Overview.mp4 3.4 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/exercise.7z 3.4 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/4. Version Check.mp4 3.4 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/5. Evaluating a Detector.mp4 3.3 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/8. What Comes Next.mp4 3.3 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/1. Course Overview/1. Course Overview.mp4 3.3 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/3. Case Study - Recommendation Systems/4. Tips for Success.mp4 3.3 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/1. Course Overview/1. Course Overview.mp4 3.3 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/4. Collaborative Filtering.mp4 3.3 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/5. Demo - Exploratory Data Analysis.mp4 3.1 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/1. Course Overview/1. Course Overview.mp4 3.1 MB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/1. Course Overview/1. Course Overview.mp4 3.1 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/5. Integrating Deep Learning in Customer Engagement.mp4 3.1 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/02. STL Decomposition.mp4 3.0 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/1. Course Overview/1. Course Overview.mp4 2.9 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/02. Better Performance – When and How.mp4 2.9 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/3. Challenges for Wider Acceptance of AI in Finance.mp4 2.7 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/1. Course Overview/1. Course Overview.mp4 2.7 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/3. How to Deal with Anomalies.mp4 2.7 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/2. Overview of LSTM and GRU.mp4 2.5 MB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/3. Inferencing.mp4 2.5 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/1. Overview.mp4 2.4 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/1. Course Overview/1. Course Overview.mp4 2.3 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/1. Course Overview/1. Course Overview.mp4 2.2 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/5. Outline of the Course.mp4 2.2 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/1. Course and Module Overview.mp4 2.2 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/1. Welcome!.mp4 2.2 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/01. Module Introduction.mp4 2.1 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/05. CNN - Pooling.mp4 2.1 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/8. Summary.mp4 2.0 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/10. Module Summary.mp4 2.0 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/1. Overview.mp4 1.9 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/10. Summary and Up Next.mp4 1.8 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/10. Summary.mp4 1.8 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/3. Factors Impacting a Stock.mp4 1.8 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/9. Summary.mp4 1.8 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/8. Summary.mp4 1.8 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/5. Key Takeaways and Tips.mp4 1.7 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/1. Overview.mp4 1.7 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/1. Overview.mp4 1.7 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/1. Module Overview.mp4 1.6 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/7. Module Summary.mp4 1.6 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/01. Module Overview.mp4 1.6 MB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/2. Demo - Introducing Globomantics Case Study.mp4 1.6 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/1. Overview.mp4 1.6 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/7. Summary and Up Next.mp4 1.5 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/5. Module Summary and Feedback.mp4 1.5 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/01. Module Introduction.mp4 1.5 MB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/06. CNN - Classification.mp4 1.5 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/6. Module Summary.mp4 1.4 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/1. Overview.mp4 1.4 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/4. Module Summary and Feedback.mp4 1.4 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/5. Summary.mp4 1.4 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/1. Module Overview.mp4 1.2 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/1. Overview.mp4 1.2 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/6. Summary.mp4 1.1 MB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/7. Summary.mp4 1.1 MB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/1. Module Overview.mp4 1.1 MB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/8. Summary.mp4 1.1 MB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/7. Module Summary.mp4 1.1 MB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/8. Summary.mp4 1.1 MB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/2. LSTM Advantages.mp4 1.0 MB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/1. Module Overview.mp4 845.7 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/4. Summary.mp4 696.2 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/7. Summary.mp4 642.2 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/7. Course Summary.mp4 633.4 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/5. Summary.mp4 621.8 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/4. Finalizing Your Dataset.mp4 621.5 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/1. Module Overview.mp4 581.1 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/6. Summary.mp4 451.1 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/2. Drift, Retaining, and Model Store.vtt 18.2 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/1. Deployment and MLOps.vtt 15.0 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/4. Training a Model - Scripted and PaaS.vtt 14.8 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/6. Demo - Training a CBOW Embedding.vtt 14.6 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/2. Demo - Fine Tuning Glove and FastText.vtt 13.3 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/4. Recurrent Neural Networks (RNNs).vtt 12.7 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/3. Demo - Bringing It into Practice.vtt 11.6 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/3. Demo - Using OHE.vtt 11.5 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/2. Understanding Model-based Collaborative Filtering.vtt 11.2 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/6. Demo - Item-based Collaborative Filtering.vtt 11.2 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/4. Demo - Dataset Introduction and Exploratory Data Analysis.vtt 11.1 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/5. Long Short-term Memory Networks (LSTMs).vtt 11.1 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/1. Detector Models, Frameworks, and Libraries.vtt 11.0 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/5. Demo - User-based Collaborative Filtering.vtt 10.8 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/07. Demo - Exploratory Data Analysis and Data Cleaning.vtt 10.6 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/5. Functions to Preprocess the Dataset.vtt 10.6 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/3. What Is Deep Learning.vtt 10.5 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/2. Implementation.vtt 10.5 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/3. Tokenization, Vocabulary, and N-grams.vtt 10.4 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/06. Demo - Image Augmentation and Hyperparameter Tuning.vtt 10.1 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/2. Demo - Load and Explore the Dataset.vtt 10.1 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/4. Demo - Book Recommendations with Deep Learning.vtt 9.7 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/4. Understanding the Three Stages of Conversational Artificial Intelligence.vtt 9.7 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/4. Demo - Debiase Word Embeddings.vtt 9.6 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/3. Evaluation Metrics for Image Captioning.vtt 9.4 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/7. Case study - Automated Medical Coding.vtt 8.9 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/2. Introduction to Healthcare Data.vtt 8.9 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/7. Demo - Reanalyze Sentiment with a Network-based Embedding.vtt 8.7 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/4. Clean the Email Dataset.vtt 8.7 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/6. Networks Architectures Using LSTMs.vtt 8.6 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/2. Introduction to Neural Networks.vtt 8.4 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/5. Image Analysis.vtt 8.3 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/4. Demo - Analyzing Sentiment with OHE.vtt 8.3 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/2. Demo - Evaluating the Anomaly Detection Models.vtt 8.3 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/1. Use Case - Customer Segmentation.vtt 8.2 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/3. Exploring Data Driven Trends in Marketing.vtt 8.1 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/6. Device Data.vtt 8.0 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/3. Demo - Movie Recommendations with SVD.vtt 8.0 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/09. Demo - Building a Model for Anomaly Detection.vtt 7.9 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/1. Module and Project Overview.vtt 7.9 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/3. Demo - Making Word Clusters.vtt 7.8 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/3. Medical Coding.vtt 7.6 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/3. Demo - Pre-processing the Images Data.vtt 7.6 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/1. Building a Foundation.vtt 7.6 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/08. Demo - Data Preprocessing and Dimensionality Reduction.vtt 7.5 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/5. Data Collection.vtt 7.4 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/5. Summary/1. Summary.vtt 7.4 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/6. Case Study - Diagnostic Image Analysis.vtt 7.4 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/2. Network Architecture for Text Generation.vtt 7.4 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/7. Generate Auto-complete Suggestions.vtt 7.2 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/6. Demo - Preprocessing and Preparing the Dataset.vtt 7.1 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/2. Building up Your Dataset.vtt 7.1 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/3. Case Study - Recommendation Systems/1. Framing the Problem.vtt 6.8 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/03. Procuring Additional Training Data - Image Augmentation.vtt 6.8 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/6. Preprocess the Email Dataset.vtt 6.6 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/5. Recommender Systems - Business Use Cases.vtt 6.6 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/4. Document and Text Analysis.vtt 6.5 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/3. Results.vtt 6.5 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/4. Demo - Pre-processing the Captions Data.vtt 6.5 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/2. What Is Time Series Data.vtt 6.5 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/4. Stationarity and Autocorrelation.vtt 6.5 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/6. Build and Train the Model.vtt 6.5 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/04. CNN - Activation.vtt 6.4 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/6. Current Trends.vtt 6.4 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/4. Proposed Solutions for Image Captioning Case Study.vtt 6.4 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/07. Demo - Creating the CNN Architecture.vtt 6.4 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/4. Handle Variable Sentence Lengths.vtt 6.2 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/4. Bias.vtt 6.2 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/5. Training Embeddings with Networks - CBOW and Skip-gram.vtt 5.9 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/03. CNN - Convolutions.vtt 5.8 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/3. Content-based Filtering.vtt 5.8 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/2. DataFormats and Computing.vtt 5.7 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/2. Demo - Build the Attention Model for Image-captioning Using TensorFlow.vtt 5.7 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/07. What Is Transfer Learning.vtt 5.7 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/3. Interpretability.vtt 5.7 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/3. Natural Language Text as Sequential Data.vtt 5.6 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/3. General Object Detection Script Setup.vtt 5.6 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/2. Decision Support vs. Decision Making.vtt 5.6 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/4. Demo - Organizing the Dataset.vtt 5.6 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/08. Transfer Learning – When and How.vtt 5.5 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/7. Understanding Generative Adversarial Networks.vtt 5.5 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/5. Peer Review.vtt 5.5 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/2. Understanding Memory-based Collaborative Filtering.vtt 5.4 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/03. Classification and Regression Trees (CART).vtt 5.4 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/3. Case Study - Recommendation Systems/3. Results.vtt 5.3 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/3. Analysing Time Series Data.vtt 5.3 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/7. Natural Language Generation Using LSTMs.vtt 5.3 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/2. Use Case - Inventory Management.vtt 5.3 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/6. Case study - Sepsis Algorithm.vtt 5.2 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/4. Demo - Input Data of Tesla Stock.vtt 5.0 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/3. Extract Plaintext Messages from Raw Email Data.vtt 4.9 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/5. Introduction to Anomaly Detection.vtt 4.8 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/05. Overfitting and Underfitting.vtt 4.6 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/3. Case Study - Recommendation Systems/2. Implementation.vtt 4.5 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/1. Discussing the Importance of Neural Network in Finance.vtt 4.5 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/04. Clustering-based Anomaly Detection.vtt 4.5 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/2. What Are We Trying to Solve.vtt 4.5 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/4. Use Case - Price Optimization.vtt 4.4 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/04. Hyperparameter Tuning.vtt 4.4 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/2. What Are Recommendation Systems.vtt 4.4 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/09. Demo - Improving Performance through Transfer Learning.vtt 4.3 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/2. Deep Learning in Retail Applications/3. Use Case - Product Image Classification.vtt 4.2 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/6. Demo - Setting up Your Environment.vtt 4.2 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/5. Predictors and Labels for Training.vtt 4.1 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/4. Getting Started with Artificial Intelligence.vtt 4.1 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/1. Course and Module Introduction.vtt 4.1 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/4. Advantages.vtt 4.1 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/5. Disadvantages.vtt 4.0 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/5. Demo - Exploring the Dataset.vtt 4.0 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/09. Demo - Performance Metrics - How Well Did Your Model Do.vtt 4.0 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/5. Demo - Prepare Training Data Using Pre-processed Data.vtt 4.0 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/1. Framing the Problem.vtt 3.9 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/3. Demo - Setting up Your Environment.vtt 3.9 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/6. Introducing Deep Learning.vtt 3.9 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/3. Case Study - Recommendation Systems/4. Tips for Success.vtt 3.9 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/2. Meshed Memory Transformer for Image Captioning.vtt 3.9 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/2. Explore Enron Email Dataset.vtt 3.9 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/3. Demo - Setting up Your Environment.vtt 3.8 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/2. The Power of Deep Learning.vtt 3.8 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/4. Tips for Success.vtt 3.8 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/5. Getting Acquainted with Machine Learning.vtt 3.7 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/2. Importance of Back Propagation.vtt 3.7 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/05. Anomaly Detection Using Autoencoders.vtt 3.6 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/2. Introducing Customer Engagement Marketing.vtt 3.5 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/6. Demo - Perform Model Training.vtt 3.5 kB
  • ~i.txt 3.5 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/06. Demo - Introduction to the Problem and Dataset.vtt 3.4 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/4. Risks and Problems Associated with Finance Industry.vtt 3.4 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/2. What Is Image Captioning and Why Is It Important.vtt 3.3 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/2. Introducing Data Driven Marketing.vtt 3.3 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/7. Understanding Deep Learning Applications in Marketing.vtt 3.3 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/1. Challenges of RNN.vtt 3.2 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/1. Course and Module Summary.vtt 3.2 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/3. Understanding CNN and RNN.vtt 3.1 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/1. How to Represent Words.vtt 3.1 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/8. Utilizing Generative Adversarial Networks in Personalized Interactions.vtt 3.1 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/4. Demo - Training Stacked LSTM Model.vtt 3.0 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/5. Evaluating a Detector.vtt 3.0 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/3. How to Deal with Anomalies.vtt 3.0 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/02. What Are Convolutional Neural Networks.vtt 3.0 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/2. Fundamentals of Deep Learning/1. Welcome!.vtt 3.0 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/1. Overview.vtt 3.0 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/1. Parameters Impacting the Stock Price of Tesla.vtt 2.9 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/4. Collaborative Filtering.vtt 2.9 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/3. Getting the Best out of This Course.vtt 2.8 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/02. Better Performance – When and How.vtt 2.8 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/3. Explaining Conversational Artificial Intelligence.vtt 2.8 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/1. Why Should We Process Text.vtt 2.8 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/5. Demo - Evaluate the Model to Predict Future Price of Tesla Stock.vtt 2.8 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/5. Demo - Define the Loss Function and Model Checkpoints.vtt 2.7 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/playlist.m3u 2.7 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/1. Course Overview/1. Course Overview.vtt 2.7 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/2. First Embedding - One Hot Encoding.vtt 2.6 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/5. Summary.vtt 2.6 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/1. Course Overview/1. Course Overview.vtt 2.6 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/1. Course Overview/1. Course Overview.vtt 2.5 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/1. Why Would We Fine Tune Existing Models.vtt 2.5 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/6. Introducing Personalized Customer Interactions.vtt 2.5 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/4. Bottom-up and Top-down Attention for Image Captioning.vtt 2.4 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/1. Course Overview/1. Course Overview.vtt 2.4 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/playlist.m3u 2.4 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/4. Demo - Implement RNN Decoder with Attention & Sentence Generator.vtt 2.4 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/02. STL Decomposition.vtt 2.4 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/3. Introducing the Business Case Study for Image-captioning.vtt 2.3 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/08. Demo - Training the Model.vtt 2.3 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/playlist.m3u 2.3 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/3. Challenges for Wider Acceptance of AI in Finance.vtt 2.2 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/1. Course Overview/1. Course Overview.vtt 2.2 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/1. Course Overview/1. Course Overview.vtt 2.2 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/5. Integrating Deep Learning in Customer Engagement.vtt 2.2 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/6. Demo - Preparing Training and Test Dataset.vtt 2.1 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/1. Course Overview/1. Course Overview.vtt 2.0 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/1. Course and Module Overview.vtt 2.0 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/playlist.m3u 2.0 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/1. Course Overview/1. Course Overview.vtt 2.0 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/05. CNN - Pooling.vtt 2.0 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/8. What Comes Next.vtt 2.0 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/4. Version Check.vtt 2.0 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/playlist.m3u 2.0 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/playlist.m3u 2.0 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/10. Summary.vtt 2.0 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/1. Course Overview/1. Course Overview.vtt 2.0 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/8. Summary.vtt 1.9 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/6. Where to Go Next.vtt 1.8 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/2. Overview of LSTM and GRU.vtt 1.8 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/10. Module Summary.vtt 1.8 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/01. Module Introduction.vtt 1.8 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/1. Overview.vtt 1.8 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/8. Summary.vtt 1.8 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/1. Course Overview/1. Course Overview.vtt 1.8 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/~i.txt 1.8 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/5. Outline of the Course.vtt 1.7 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/5. Demo - Exploratory Data Analysis.vtt 1.7 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/7. Demo - Making Predictions out of the Trained Model.vtt 1.7 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/~i.txt 1.7 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/1. Overview.vtt 1.7 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/~i.txt 1.7 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/1. Overview.vtt 1.7 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/10. Summary and Up Next.vtt 1.6 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/~i.txt 1.6 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/~i.txt 1.6 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/3. Factors Impacting a Stock.vtt 1.6 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/~i.txt 1.6 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/1. Module Overview.vtt 1.6 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/5. Module Summary and Feedback.vtt 1.5 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/playlist.m3u 1.5 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/2. Introduction to Time Series Data and Anomaly Detection/7. Module Summary.vtt 1.5 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/3. Inferencing.vtt 1.5 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/1. Overview.vtt 1.5 kB
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/~i.txt 1.5 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/~i.txt 1.5 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/4. Module Summary and Feedback.vtt 1.4 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/7. Summary and Up Next.vtt 1.4 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/3. Demo - Implement CNN Encoder in TensorFlow.vtt 1.4 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/1. Course Overview/1. Course Overview.vtt 1.4 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/~i.txt 1.4 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/01. Module Introduction.vtt 1.4 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/2. Getting Started with Recommender Systems/6. Module Summary.vtt 1.4 kB
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/01. Module Overview.vtt 1.3 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/playlist.m3u 1.3 kB
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/~i.txt 1.3 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/9. Summary.vtt 1.3 kB
  • B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/06. CNN - Classification.vtt 1.3 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/1. Module Overview.vtt 1.3 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/1. Overview.vtt 1.2 kB
  • B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/7. Summary.vtt 1.2 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/2. Why Process Text/2. Demo - Introducing Globomantics Case Study.vtt 1.1 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/3. Healthcare Data/1. Module Overview.vtt 1.1 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/playlist.m3u 1.1 kB
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/~i.txt 1.1 kB
  • C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/5. Key Takeaways and Tips.vtt 1.1 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/2. Introducing Image Captioning/5. Summary.vtt 1.0 kB
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/7. Course Summary.vtt 1.0 kB
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/1. Overview.vtt 1.0 kB
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/2. LSTM Advantages.vtt 1.0 kB
  • C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/7. Module Summary.vtt 981 Bytes
  • A4. Deep Learning Application for Retail (Trent McMillan, 2022)/playlist.m3u 979 Bytes
  • C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/1. Module Overview.vtt 979 Bytes
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/6. Summary.vtt 949 Bytes
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/8. Summary.vtt 919 Bytes
  • A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/1. Overview.vtt 870 Bytes
  • B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/8. Summary.vtt 855 Bytes
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/4. Summary.vtt 759 Bytes
  • A1. Deep Learning Application for Healthcare (Colin Matthews, 2022)/4. Ethics in Healthcare AI/1. Module Overview.vtt 745 Bytes
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/playlist.m3u 741 Bytes
  • C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/4. Finalizing Your Dataset.vtt 688 Bytes
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/2. Understanding the Applications of Deep Learning Algorithms in Finance World/5. Summary.vtt 669 Bytes
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/7. Summary.vtt 623 Bytes
  • A3. Deep Learning Application for Finance (Jaimin M, 2022)/4. Predicting Stock Price Using Stacked LSTM/6. Summary.vtt 505 Bytes

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