[CourseClub.Me] Pluralsight - Building Machine Learning Solutions With Java - Learning Paths

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[CourseClub.Me] Pluralsight - Building Machine Learning Solutions With Java - Learning Paths

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收录时间：2024-01-10
最近下载：2025-05-20

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文件列表

  • 2. Exploring Java Machine Learning Environments/exercise.zip 86.3 MB
  • 1. Preparing Data for Machine Learning with Java/5. Data Transformation/4. Demo - Data Transformation Pipeline.mp4 36.0 MB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/5. Demo - Developing Beam SDK Pipelines.mp4 35.9 MB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/4. Demo - Data Preprocessing with DL4J.mp4 33.5 MB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/5. Demo - Ingestion.mp4 30.1 MB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/3. Demo - Data Preparation and Loading with DL4J (Part 2 - DL4J DataSetIt.mp4 29.5 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/8. Demo - Coding for Selenium.mp4 28.3 MB
  • 1. Preparing Data for Machine Learning with Java/exercise.zip 27.3 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/4. Demo - Using the File Watcher API.mp4 27.2 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/3. Demo - Visualizing Cluster Assignments.mp4 26.0 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/08. Demo - Training and Evaluating a Multiple Regression Model.mp4 26.0 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/5. Demo - Using the Quartz Scheduler Library.mp4 25.9 MB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/5. Demo - Performing Classification on Text Data.mp4 24.9 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/09. Demo - Feature Selection and Ranking.mp4 24.2 MB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/4. Demo - Encoding Text Data in Numeric Form.mp4 24.0 MB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/2. Demo - Building and Evaluating a Classification Model.mp4 23.5 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/8. Demo - Deploying a Model Using SpringBoot.mp4 22.9 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/07. Demo - Building and Evaluating a Logistic Regression Classification .mp4 22.7 MB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/1. Demo - Feature Selection and Data Processing.mp4 22.2 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/03. Demo - Loading and Exploring Data.mp4 22.2 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/09. Demo - Performing Clustering and Evaluating Clustering Models.mp4 22.1 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/13. Demo - Serializing and Visualizing a Decision Tree Model.mp4 21.9 MB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/5. Demo - Implementing a Twitter Sentiment Classifier with DL4J.mp4 21.4 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/10. Demo - Processing and Saving Processed Data.mp4 21.3 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/1. Demo - Normalizing and Visualizing Data.mp4 21.0 MB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/5. Demo - Data Cleaning Pipeline.mp4 20.6 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/06. Demo - Exploring the Dataset.mp4 20.0 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/12. Demo - Train a Model with Normalized Data.mp4 19.5 MB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/3. Demo - Data Preprocessing with Spark MLlib.mp4 19.3 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/07. Demo - Training and Evaluating a Regression Model.mp4 19.0 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/06. Demo - Performing Predictions Using the Classification Model.mp4 18.2 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/11. Demo - Assign Roles and Perform Attribute Selection.mp4 17.3 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/04. Demo - Building and Training a Regression Model.mp4 17.1 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/09. Demo - Using a Pretrained Model for Image Segmentation.mp4 16.8 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/02. Demo - Getting Set up with a Maven Project.mp4 16.8 MB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/5. Demo - Spark MLlib Showcase.mp4 16.7 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/07. Demo - Build and Evaluate a Linear Regression Model.mp4 16.4 MB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/5. Demo - Evaluation and Visualization with Programmatic Weka.mp4 16.2 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/11. Demo - Making Predictions Using a Deployed Model.mp4 16.1 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/05. Demo - Exploring the Weka Workbench.mp4 15.7 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/10. Demo - Evaluate a Model Using Cross-validation.mp4 15.7 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/5. Demo - Performing Hierarchical Clustering.mp4 15.7 MB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/1. Introduction.mp4 15.6 MB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/4. Demo - Deeplearning4j (DL4J) Showcase.mp4 15.5 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/06. Demo - Loading and Exploring the Dataset.mp4 15.4 MB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/3. Demo - Building and Visualizing a Decision Tree Model.mp4 15.4 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/10. Demo - Serializing and Deserializing Trained Models.mp4 15.0 MB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/1. Introduction.mp4 14.6 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/04. Demo - Building a Fully Connected Neural Network for Image Classifica.mp4 14.2 MB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/6. Demo - Deploying Beam SDK Pipelines to GCP Dataflow.mp4 14.2 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/08. Demo - Using a Pretrained Model for Image Classification.mp4 13.7 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/05. Demo - Setting up a Repository and Importing Data.mp4 13.4 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/7. Demo - Serializing Trained Model Parameters.mp4 13.2 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/2. Demo - Performing K-means Clustering.mp4 13.0 MB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/2. Demo - Data Preparation and Loading with DL4J (Part 1 - Setup).mp4 12.8 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/06. Demo - Training and Evaluating a Ridge Regression Model.mp4 12.7 MB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/2. Demo - Data Preparation and Loading with Spark MLlib.mp4 12.7 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/05. Demo - Evaluating a Regression Model.mp4 12.7 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/1. Introduction.mp4 12.6 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/12. Demo - Regression Using Support Vector Machines and Multilayer Perceptrons.mp4 12.4 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/11. Demo - Answering Questions with Google BERT.mp4 12.3 MB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/1. Introduction.mp4 12.3 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/09. Demo - Perform Attribute Selection.mp4 11.9 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/04. Demo - Environment and Project Setup.mp4 11.7 MB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/3. Ingesting CSV and Excel Files.mp4 11.5 MB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/6. Demo - The Full Workflow in One Go with Weka GUI.mp4 11.4 MB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/3. Demo - Weka Showcase.mp4 10.9 MB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/2. Demo - Data Preparation and Loading with Programmatic Weka.mp4 10.9 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/04. Demo - Download and Setup RapidMiner.mp4 10.9 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/08. Demo - Train Model on Training Data and Evaluate Using T.mp4 10.8 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/6. Demo - Performing EM Clustering.mp4 10.8 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/4. Demo - Exploring and Visualizing Data.mp4 10.4 MB
  • 1. Preparing Data for Machine Learning with Java/5. Data Transformation/3. Scaling, Data Skew, and Data Bias.mp4 10.3 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/2. Folder Monitoring.mp4 10.1 MB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/4. Beam SDK Engines and GCP Dataflow.mp4 9.9 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/05. Demo - Training the Image Classification Model.mp4 9.4 MB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/2. Lambdas and Streams.mp4 9.2 MB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/4. Using Regular Expressions in Java.mp4 8.9 MB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/1. Introduction.mp4 8.8 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/11. Demo - Evaluating a Model Using Cross Validation.mp4 8.1 MB
  • 1. Preparing Data for Machine Learning with Java/5. Data Transformation/1. Introduction.mp4 7.9 MB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/4. Ingesting JSON and XML Files.mp4 7.9 MB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/1. Introduction.mp4 7.9 MB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/5. Demo - Performance and Evaluation and Visualization with Spark .mp4 7.8 MB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/3. Regular Expressions Overview.mp4 7.8 MB
  • 1. Preparing Data for Machine Learning with Java/5. Data Transformation/2. Data Transformation Basics.mp4 7.8 MB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/1. Introduction.mp4 7.6 MB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/3. Beam SDK Concepts.mp4 7.2 MB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/6. Demo - Performance and Evaluation and Visualization with DL4J.mp4 6.9 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/7. Demo - Using the Selenium IDE.mp4 6.9 MB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/2. Introduction.mp4 6.8 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/08. Demo - Building and Evaluating a Decision Tree Classification Model.mp4 6.7 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/07. Brief Overview of Transfer Learning.mp4 6.5 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/3. Task Scheduling.mp4 6.4 MB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/4. Demo - Implementing an Image Classifier with Spark MLlib.mp4 6.0 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/6. Selenium.mp4 5.9 MB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/2. Distributed Data Pipelines.mp4 5.9 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/01. Introducing DJL.mp4 5.7 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/01. Introducing JSAT.mp4 5.6 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/03. Demo - Setting up the Maven Project and Dependencies.mp4 5.5 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/02. Brief Overview of Neural Networks.mp4 5.4 MB
  • 1. Preparing Data for Machine Learning with Java/1. Course Overview/1. Course Overview.mp4 4.9 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/03. Introducing RapidMiner.mp4 4.6 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/exercise.zip 4.6 MB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/3. Demo - Data Preprocessing with Programmatic Weka.mp4 4.3 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/1. Course Overview/1. Course Overview.mp4 4.2 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/03. Introducing Weka.mp4 4.2 MB
  • 3. Implementing Machine Learning Workflow with Weka/1. Course Overview/1. Course Overview.mp4 4.2 MB
  • 2. Exploring Java Machine Learning Environments/1. Course Overview/1. Course Overview.mp4 4.0 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/02. Prerequisites and Course Outline.mp4 4.0 MB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/02. Prerequisites and Course Outline.mp4 3.8 MB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/4. Demo - Implementing K-means with Programmatic Weka.mp4 3.8 MB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/8. Wrap Up.mp4 2.9 MB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/6. Summary.mp4 2.7 MB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/9. Summary and Further Study.mp4 2.7 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/12. Summary and Further Study.mp4 2.6 MB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/10. Introducing Google BERT.mp4 2.4 MB
  • 3. Implementing Machine Learning Workflow with Weka/exercise.zip 2.3 MB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/2. What Is Data Preparation.mp4 2.0 MB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/7. Summary.mp4 1.2 MB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/9. Summary.mp4 1.1 MB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/6. Summary.mp4 1.1 MB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/7. Summary.mp4 1.0 MB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/7. Summary.mp4 977.8 kB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/6. Summary.mp4 966.0 kB
  • 1. Preparing Data for Machine Learning with Java/5. Data Transformation/5. Summary.mp4 837.8 kB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/6. Summary.mp4 655.5 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/01. Version Check.mp4 559.6 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/01. Version Check.mp4 528.6 kB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/1. Version Check.mp4 384.9 kB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/4. Demo - Data Preprocessing with DL4J.vtt 10.2 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/06. Demo - Exploring the Dataset.vtt 10.2 kB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/5. Demo - Performing Classification on Text Data.vtt 10.1 kB
  • 1. Preparing Data for Machine Learning with Java/5. Data Transformation/4. Demo - Data Transformation Pipeline.vtt 10.0 kB
  • 1. Preparing Data for Machine Learning with Java/5. Data Transformation/3. Scaling, Data Skew, and Data Bias.vtt 9.6 kB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/8. Demo - Deploying a Model Using SpringBoot.vtt 9.5 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/09. Demo - Feature Selection and Ranking.vtt 9.4 kB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/2. Folder Monitoring.vtt 9.2 kB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/4. Beam SDK Engines and GCP Dataflow.vtt 9.2 kB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/1. Demo - Feature Selection and Data Processing.vtt 9.1 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/12. Demo - Train a Model with Normalized Data.vtt 9.1 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/06. Demo - Performing Predictions Using the Classification Model.vtt 9.0 kB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/2. Lambdas and Streams.vtt 8.9 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/13. Demo - Serializing and Visualizing a Decision Tree Model.vtt 8.9 kB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/1. Demo - Normalizing and Visualizing Data.vtt 8.7 kB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/3. Ingesting CSV and Excel Files.vtt 8.7 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/04. Demo - Building a Fully Connected Neural Network for Image Classifica.vtt 8.7 kB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/5. Demo - Developing Beam SDK Pipelines.vtt 8.6 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/09. Demo - Performing Clustering and Evaluating Clustering Models.vtt 8.6 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/11. Demo - Making Predictions Using a Deployed Model.vtt 8.5 kB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/2. Demo - Building and Evaluating a Classification Model.vtt 8.4 kB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/5. Demo - Ingestion.vtt 8.4 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/07. Demo - Building and Evaluating a Logistic Regression Classification .vtt 8.3 kB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/3. Demo - Data Preparation and Loading with DL4J (Part 2 - DL4J DataSetIt.vtt 8.3 kB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/4. Demo - Using the File Watcher API.vtt 8.2 kB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/3. Demo - Visualizing Cluster Assignments.vtt 8.0 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/07. Demo - Build and Evaluate a Linear Regression Model.vtt 7.8 kB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/5. Demo - Data Cleaning Pipeline.vtt 7.7 kB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/8. Demo - Coding for Selenium.vtt 7.7 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/11. Demo - Assign Roles and Perform Attribute Selection.vtt 7.5 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/05. Demo - Exploring the Weka Workbench.vtt 7.4 kB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/4. Using Regular Expressions in Java.vtt 7.4 kB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/4. Demo - Encoding Text Data in Numeric Form.vtt 7.3 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/03. Demo - Loading and Exploring Data.vtt 7.2 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/07. Demo - Training and Evaluating a Regression Model.vtt 7.1 kB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/3. Demo - Data Preprocessing with Spark MLlib.vtt 7.1 kB
  • 1. Preparing Data for Machine Learning with Java/5. Data Transformation/2. Data Transformation Basics.vtt 7.1 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/08. Demo - Training and Evaluating a Multiple Regression Model.vtt 7.1 kB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/5. Demo - Performing Hierarchical Clustering.vtt 7.0 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/09. Demo - Using a Pretrained Model for Image Segmentation.vtt 7.0 kB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/5. Demo - Using the Quartz Scheduler Library.vtt 7.0 kB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/1. Introduction.vtt 6.7 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/10. Demo - Evaluate a Model Using Cross-validation.vtt 6.5 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/04. Demo - Building and Training a Regression Model.vtt 6.4 kB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/6. Demo - Deploying Beam SDK Pipelines to GCP Dataflow.vtt 6.4 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/10. Demo - Processing and Saving Processed Data.vtt 6.3 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/08. Demo - Using a Pretrained Model for Image Classification.vtt 6.2 kB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/2. Demo - Data Preparation and Loading with Spark MLlib.vtt 6.0 kB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/5. Demo - Implementing a Twitter Sentiment Classifier with DL4J.vtt 6.0 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/02. Demo - Getting Set up with a Maven Project.vtt 5.9 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/05. Demo - Setting up a Repository and Importing Data.vtt 5.9 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/04. Demo - Environment and Project Setup.vtt 5.7 kB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/3. Demo - Weka Showcase.vtt 5.7 kB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/4. Ingesting JSON and XML Files.vtt 5.7 kB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/3. Beam SDK Concepts.vtt 5.7 kB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/1. Introduction.vtt 5.6 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/10. Demo - Serializing and Deserializing Trained Models.vtt 5.6 kB
  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/6. Demo - The Full Workflow in One Go with Weka GUI.vtt 5.6 kB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/2. Introduction.vtt 5.5 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/09. Demo - Perform Attribute Selection.vtt 5.5 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/06. Demo - Loading and Exploring the Dataset.vtt 5.4 kB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/2. Demo - Performing K-means Clustering.vtt 5.3 kB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/3. Regular Expressions Overview.vtt 5.3 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/04. Demo - Download and Setup RapidMiner.vtt 5.3 kB
  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/2. Demo - Data Preparation and Loading with DL4J (Part 1 - Setup).vtt 5.3 kB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/1. Introduction.vtt 5.3 kB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/2. Distributed Data Pipelines.vtt 5.3 kB
  • 3. Implementing Machine Learning Workflow with Weka/3. Implementing Classification Models/3. Demo - Building and Visualizing a Decision Tree Model.vtt 5.2 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/06. Demo - Training and Evaluating a Ridge Regression Model.vtt 5.2 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/11. Demo - Answering Questions with Google BERT.vtt 5.2 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/12. Demo - Regression Using Support Vector Machines and Multilayer Perceptrons.vtt 5.1 kB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/6. Demo - Performing EM Clustering.vtt 5.1 kB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/4. Demo - Deeplearning4j (DL4J) Showcase.vtt 5.1 kB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/6. Selenium.vtt 5.1 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/08. Demo - Train Model on Training Data and Evaluate Using T.vtt 5.0 kB
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  • 2. Exploring Java Machine Learning Environments/3. Implementing a Machine Learning Workflow with Weka/5. Demo - Evaluation and Visualization with Programmatic Weka.vtt 4.9 kB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/3. Task Scheduling.vtt 4.8 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/05. Demo - Training the Image Classification Model.vtt 4.8 kB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/4. Demo - Exploring and Visualizing Data.vtt 4.7 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/07. Brief Overview of Transfer Learning.vtt 4.7 kB
  • 3. Implementing Machine Learning Workflow with Weka/4. Implementing Clustering Models/7. Demo - Serializing Trained Model Parameters.vtt 4.6 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/01. Introducing DJL.vtt 4.6 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/03. Using JSAT to Implement Machine Learning Models/01. Introducing JSAT.vtt 4.5 kB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/5. Demo - Spark MLlib Showcase.vtt 4.4 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/04. Using DJL to Implement Machine Learning Models/02. Brief Overview of Neural Networks.vtt 4.4 kB
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  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/03. Introducing RapidMiner.vtt 3.9 kB
  • 1. Preparing Data for Machine Learning with Java/2. Ingesting Data from Files in Various Formats/1. Introduction.vtt 3.9 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/playlist.m3u 3.8 kB
  • 1. Preparing Data for Machine Learning with Java/6. Data Preparation at Scale/1. Introduction.vtt 3.6 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/02. Implementing Machine Learning Models with RapidMiner Studio/02. Prerequisites and Course Outline.vtt 3.6 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/02. Prerequisites and Course Outline.vtt 3.4 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/03. Introducing Weka.vtt 3.4 kB
  • 1. Preparing Data for Machine Learning with Java/3. Automating Data Collection and Scheduling/1. Introduction.vtt 3.2 kB
  • 4. Implementing Machine Learning Workflow with RapidMiner/1. Course Overview/1. Course Overview.vtt 3.2 kB
  • 3. Implementing Machine Learning Workflow with Weka/1. Course Overview/1. Course Overview.vtt 3.2 kB
  • 1. Preparing Data for Machine Learning with Java/4. Data Cleaning Using Regex and Formatter/1. Introduction.vtt 3.0 kB
  • 3. Implementing Machine Learning Workflow with Weka/02. Implementing Regression Models/11. Demo - Evaluating a Model Using Cross Validation.vtt 2.7 kB
  • 2. Exploring Java Machine Learning Environments/2. Understanding the Java Machine Learning Ecosystem/6. Summary.vtt 2.7 kB
  • 2. Exploring Java Machine Learning Environments/playlist.m3u 2.6 kB
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  • 2. Exploring Java Machine Learning Environments/4. Implementing a Machine Learning Workflow with DL4J/6. Demo - Performance and Evaluation and Visualization with DL4J.vtt 2.6 kB
  • 2. Exploring Java Machine Learning Environments/5. Implementing a Machine Learning Workflow with Spark MLlib/4. Demo - Implementing an Image Classifier with Spark MLlib.vtt 2.6 kB
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