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种子名称： [FreeCourseLab.com] Udemy - Data Science Deep Learning in Python
文件类型： 视频
文件数目： 82个文件
文件大小： 1.44 GB
收录时间： 2019-3-5 19:41
已经下载： 3次
资源热度： 85
最近下载： 2024-10-5 18:35

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[FreeCourseLab.com] Udemy - Data Science Deep Learning in Python.torrent

1. Welcome/1. Introduction and Outline.mp46.09MB

1. Welcome/2. Where does this course fit into your deep learning studies.mp454.08MB

1. Welcome/3. Where to get the code.mp423.37MB

1. Welcome/4. How to Succeed in this Course.mp417.43MB

10. Appendix/1. What is the Appendix.mp45.45MB

10. Appendix/10. How to Uncompress a .tar.gz file.mp45.44MB

10. Appendix/11. BONUS Where to get Udemy coupons and FREE deep learning material.mp44.02MB

10. Appendix/12. Python 2 vs Python 3.mp47.84MB

10. Appendix/13. Where does this course fit into your deep learning studies (Old Version).mp48.46MB

10. Appendix/14. What order should I take your courses in (part 1).mp429.33MB

10. Appendix/15. What order should I take your courses in (part 2).mp437.62MB

10. Appendix/2. What's the difference between neural networks and deep learning.mp414.77MB

10. Appendix/3. Windows-Focused Environment Setup 2018.mp4186.36MB

10. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB

10. Appendix/5. How to Code by Yourself (part 1).mp424.53MB

10. Appendix/6. How to Code by Yourself (part 2).mp414.8MB

10. Appendix/7. How to Succeed in this Course (Long Version).mp412.99MB

10. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.96MB

10. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp478.3MB

2. Review/1. Review Section Introduction.mp412.54MB

2. Review/2. What does machine learning do.mp425.63MB

2. Review/3. Neuron Predictions.mp424.46MB

2. Review/4. Neuron Training.mp438.53MB

2. Review/5. Deep Learning Readiness Test.mp48.58MB

2. Review/6. Review Section Summary.mp414.02MB

3. Preliminaries From Neurons to Neural Networks/1. Neural Networks with No Math.mp47.35MB

3. Preliminaries From Neurons to Neural Networks/2. Introduction to the E-Commerce Course Project.mp414.8MB

4. Classifying more than 2 things at a time/1. Prediction Section Introduction and Outline.mp48.99MB

4. Classifying more than 2 things at a time/10. Building an entire feedforward neural network in Python.mp413.87MB

4. Classifying more than 2 things at a time/11. E-Commerce Course Project Pre-Processing the Data.mp411.16MB

4. Classifying more than 2 things at a time/12. E-Commerce Course Project Making Predictions.mp47.59MB

4. Classifying more than 2 things at a time/13. Prediction Quizzes.mp45.11MB

4. Classifying more than 2 things at a time/14. Prediction Section Summary.mp42.82MB

4. Classifying more than 2 things at a time/2. From Logistic Regression to Neural Networks.mp48.56MB

4. Classifying more than 2 things at a time/3. Interpreting the Weights of a Neural Network.mp412.52MB

4. Classifying more than 2 things at a time/4. Softmax.mp44.56MB

4. Classifying more than 2 things at a time/5. Sigmoid vs. Softmax.mp42.41MB

4. Classifying more than 2 things at a time/6. Feedforward in Slow-Mo (part 1).mp430.28MB

4. Classifying more than 2 things at a time/7. Feedforward in Slow-Mo (part 2).mp416.69MB

4. Classifying more than 2 things at a time/8. Where to get the code for this course.mp42.99MB

4. Classifying more than 2 things at a time/9. Softmax in Code.mp47.78MB

5. Training a neural network/1. Training Section Introduction and Outline.mp44.42MB

5. Training a neural network/10. E-Commerce Course Project Training Logistic Regression with Softmax.mp420.25MB

5. Training a neural network/11. E-Commerce Course Project Training a Neural Network.mp415.47MB

5. Training a neural network/12. Training Quiz.mp48.32MB

5. Training a neural network/13. Training Section Summary.mp44.1MB

5. Training a neural network/2. What do all these symbols and letters mean.mp414.57MB

5. Training a neural network/3. What does it mean to train a neural network.mp49.74MB

5. Training a neural network/4. How to Brace Yourself to Learn Backpropagation.mp437.32MB

5. Training a neural network/5. Backpropagation Intro.mp419.1MB

5. Training a neural network/6. Backpropagation - what does the weight update depend on.mp410.13MB

5. Training a neural network/7. Backpropagation - recursiveness.mp411.19MB

5. Training a neural network/8. Backpropagation in code.mp446.34MB

5. Training a neural network/9. The WRONG Way to Learn Backpropagation.mp46.85MB

6. Practical Machine Learning/1. Practical Issues Section Introduction and Outline.mp42.73MB

6. Practical Machine Learning/2. Donut and XOR Review.mp41.82MB

6. Practical Machine Learning/3. Donut and XOR Revisited.mp413.96MB

6. Practical Machine Learning/4. Neural Networks for Regression.mp425.38MB

6. Practical Machine Learning/5. Common nonlinearities and their derivatives.mp42.39MB

6. Practical Machine Learning/6. Practical Considerations for Choosing Activation Functions.mp412.37MB

6. Practical Machine Learning/7. Hyperparameters and Cross-Validation.mp46.95MB

6. Practical Machine Learning/8. Manually Choosing Learning Rate and Regularization Penalty.mp47.77MB

6. Practical Machine Learning/9. Practical Issues Section Summary.mp49.61MB

7. TensorFlow, exercises, practice, and what to learn next/1. TensorFlow plug-and-play example.mp415.9MB

7. TensorFlow, exercises, practice, and what to learn next/2. Visualizing what a neural network has learned using TensorFlow Playground.mp443.25MB

7. TensorFlow, exercises, practice, and what to learn next/3. Where to go from here.mp46.06MB

7. TensorFlow, exercises, practice, and what to learn next/4. You know more than you think you know.mp48.23MB

7. TensorFlow, exercises, practice, and what to learn next/5. How to get good at deep learning + exercises.mp49.45MB

7. TensorFlow, exercises, practice, and what to learn next/6. Deep neural networks in just 3 lines of code with Sci-Kit Learn.mp414.1MB

8. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp49.82MB

8. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp421.43MB

8. Project Facial Expression Recognition/3. The class imbalance problem.mp410.11MB

8. Project Facial Expression Recognition/4. Utilities walkthrough.mp413.48MB

8. Project Facial Expression Recognition/5. Facial Expression Recognition in Code (Binary Sigmoid).mp425.19MB

8. Project Facial Expression Recognition/6. Facial Expression Recognition in Code (Logistic Regression Softmax).mp419.76MB

8. Project Facial Expression Recognition/7. Facial Expression Recognition in Code (ANN Softmax).mp423.48MB

8. Project Facial Expression Recognition/8. Facial Expression Recognition Project Summary.mp42.92MB

9. Backpropagation Supplementary Lectures/1. Backpropagation Supplementary Lectures Introduction.mp41.73MB

9. Backpropagation Supplementary Lectures/2. Why Learn the Ins and Outs of Backpropagation.mp415.63MB

9. Backpropagation Supplementary Lectures/3. Gradient Descent Tutorial.mp422.84MB

9. Backpropagation Supplementary Lectures/4. Help with Softmax Derivative.mp46.28MB

9. Backpropagation Supplementary Lectures/5. Backpropagation with Softmax Troubleshooting.mp418.15MB