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6. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix/11. What order should I take your courses in (part 2).mp4 85.6 MB
6. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
6. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
6. Appendix/11. What order should I take your courses in (part 2).vtt 39.5 MB
3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.mp4 37.8 MB
1. Welcome/1. Welcome.mp4 33.6 MB
6. Appendix/10. What order should I take your courses in (part 1).mp4 30.7 MB
1. Welcome/2. Introduction and Outline.mp4 29.8 MB
2. 1-D Linear Regression Theory and Code/2. Define the model in 1-D, derive the solution.mp4 25.9 MB
6. Appendix/5. How to Code by Yourself (part 1).mp4 25.7 MB
4. Practical machine learning issues/11. Gradient Descent Tutorial.mp4 23.9 MB
2. 1-D Linear Regression Theory and Code/1. Define the model in 1-D, derive the solution (Updated Version).mp4 20.3 MB
6. Appendix/7. How to Succeed in this Course (Long Version).mp4 19.2 MB
2. 1-D Linear Regression Theory and Code/7. Demonstrating Moore's Law in Code.mp4 18.3 MB
4. Practical machine learning issues/4. Generalization and Overfitting Demonstration in Code.mp4 18.1 MB
6. Appendix/12. Python 2 vs Python 3.mp4 17.7 MB
3. Multiple linear regression and polynomial regression/5. Polynomial regression - extending linear regression (with Python code).mp4 17.2 MB
3. Multiple linear regression and polynomial regression/4. Coding the multi-dimensional solution in Python.mp4 15.6 MB

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~Get Your Files Here !/3. Dealing With File Streams.mp4 376.3 MB
~Get Your Files Here !/1. What Is Streams And Types Of Streams.mp4 242.9 MB
~Get Your Files Here !/6. Serialization And Deserialization.mp4 179.8 MB
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[ FreeCourseWeb.com ] Udemy - Deep Learning for NLP - Part 5

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~Get Your Files Here !/2. Efficient Transformers Part 2/5. Performer.mp4 176.4 MB
~Get Your Files Here !/1. Efficient Transformers Part 1/3. Sparse Transformers.mp4 147.9 MB
~Get Your Files Here !/1. Efficient Transformers Part 1/4. Reformer.mp4 142.5 MB
~Get Your Files Here !/1. Efficient Transformers Part 1/2. Star Transformers.mp4 132.1 MB
~Get Your Files Here !/2. Efficient Transformers Part 2/3. Big bird.mp4 130.3 MB
~Get Your Files Here !/1. Efficient Transformers Part 1/7. Synthesizer.mp4 121.6 MB
~Get Your Files Here !/2. Efficient Transformers Part 2/4. Linear attention Transformer.mp4 110.6 MB
~Get Your Files Here !/2. Efficient Transformers Part 2/6. Sparse Sinkhorn Transformer.mp4 98.7 MB
~Get Your Files Here !/1. Efficient Transformers Part 1/5. Longformer.mp4 90.1 MB
~Get Your Files Here !/1. Efficient Transformers Part 1/6. Linformer.mp4 84.9 MB
~Get Your Files Here !/2. Efficient Transformers Part 2/9. Comparison of various efficient Transformer methods.mp4 67.5 MB
~Get Your Files Here !/2. Efficient Transformers Part 2/8. Efficient Transformer benchmark Long Range Arena.mp4 64.9 MB
~Get Your Files Here !/2. Efficient Transformers Part 2/7. Routing transformers.mp4 64.6 MB
~Get Your Files Here !/2. Efficient Transformers Part 2/10. Summary.mp4 20.0 MB
~Get Your Files Here !/1. Efficient Transformers Part 1/1. Introduction.mp4 17.9 MB
~Get Your Files Here !/2. Efficient Transformers Part 2/1. Introduction.mp4 17.1 MB
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~Get Your Files Here !/2. Efficient Transformers Part 2/5. Performer-en_US.srt 29.6 kB

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Screenshots/I Deep Throat - Volume 2.jpeg 5.9 MB
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I Deep Throat - Volume 1.mp4 1.1 GB

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[FreeCourseSite.com] Udemy - [2022] Machine Learning and Deep Learning Bootcamp in Python

54 - COURSE MATERIALS (DOWNLOADS)/001 PythonMachineLearning.zip 592.6 MB
33 - Q Learning Implementation (Tic Tac Toe)/006 Tic tac toe with Q learning implementation VI.mp4 104.3 MB
45 - You Only Look Once (YOLO) Algorithm Implementation/005 YOLO algorithm implementation V.mp4 100.5 MB
05 - Linear Regression/004 Linear regression implementation I.mp4 95.2 MB
19 - Single Layer Networks Implementation/002 Simple neural network implementation - Iris dataset.mp4 89.1 MB
09 - Naive Bayes Classifier/006 Naive Bayes example - clustering news.mp4 82.7 MB
35 - Deep Q Learning Implementation (Tic Tac Toe)/003 Tic Tac Toe with deep Q learning implementation III.mp4 77.9 MB
40 - Face Detection with Viola-Jones Method Implementation/002 Face detection implementation II - CascadeClassifier.mp4 74.1 MB
46 - Single-Shot MultiBox Detector (SSD) Theory/003 Bounding boxes and anchor boxes.mp4 74.0 MB
45 - You Only Look Once (YOLO) Algorithm Implementation/004 YOLO algorithm implementation IV.mp4 73.1 MB
38 - Computer Vision Project I - Lane Detection Problem (Self-Driving Cars)/005 Getting the useful region of the image - masking.mp4 67.9 MB
16 - Machine Learning Project I - Face Recognition/004 Understanding eigenfaces.mp4 66.0 MB
43 - Convolutional Neural Networks (CNNs) Based Approaches/002 Region proposals and convolutional neural networks (CNNs).mp4 63.6 MB
26 - Machine Learning Project III - Identifying Objects with CNNs/004 Tuning the parameters - regularization.mp4 63.4 MB
06 - Logistic Regression/004 Logistic regression example II- credit scoring.mp4 61.4 MB
25 - Convolutional Neural Networks (CNNs) Implementation/002 Handwritten digit classification II.mp4 58.3 MB
25 - Convolutional Neural Networks (CNNs) Implementation/001 Handwritten digit classification I.mp4 57.0 MB
42 - Histogram of Oriented Gradients (HOG) Implementation/001 Showing the HOG features programatically.mp4 56.0 MB
31 - Exploration vs. Exploitation Problem/003 N-armed bandit problem implementation.mp4 55.9 MB
42 - Histogram of Oriented Gradients (HOG) Implementation/003 Face detection with HOG implementation II.mp4 54.9 MB

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