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

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

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种子哈希：bdb8622a384a13b634bddff2a728348e3e8f4a7e
文件大小： 1.44G
已经下载：115次
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收录时间：2022-03-18
最近下载：2025-02-24

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文件列表

  • 10. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.4 MB
  • 10. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
  • 1. Welcome/2. Where does this course fit into your deep learning studies.mp4 56.7 MB
  • 5. Training a neural network/8. Backpropagation in code.mp4 48.6 MB
  • 10. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
  • 7. TensorFlow, exercises, practice, and what to learn next/2. Visualizing what a neural network has learned using TensorFlow Playground.mp4 45.4 MB
  • 10. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
  • 2. Review/4. Neuron Training.mp4 40.4 MB
  • 10. Appendix/15. What order should I take your courses in (part 2).mp4 39.4 MB
  • 5. Training a neural network/4. How to Brace Yourself to Learn Backpropagation.mp4 39.1 MB
  • 4. Classifying more than 2 things at a time/6. Feedforward in Slow-Mo (part 1).mp4 31.8 MB
  • 10. Appendix/14. What order should I take your courses in (part 1).mp4 30.8 MB
  • 2. Review/2. What does machine learning do.mp4 26.9 MB
  • 6. Practical Machine Learning/4. Neural Networks for Regression.mp4 26.6 MB
  • 8. Project Facial Expression Recognition/5. Facial Expression Recognition in Code (Binary Sigmoid).mp4 26.4 MB
  • 10. Appendix/5. How to Code by Yourself (part 1).mp4 25.7 MB
  • 2. Review/3. Neuron Predictions.mp4 25.6 MB
  • 8. Project Facial Expression Recognition/7. Facial Expression Recognition in Code (ANN Softmax).mp4 24.6 MB
  • 1. Welcome/3. Where to get the code.mp4 24.5 MB
  • 9. Backpropagation Supplementary Lectures/3. Gradient Descent Tutorial.mp4 23.9 MB
  • 8. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 22.5 MB
  • 5. Training a neural network/10. E-Commerce Course Project Training Logistic Regression with Softmax.mp4 21.2 MB
  • 8. Project Facial Expression Recognition/6. Facial Expression Recognition in Code (Logistic Regression Softmax).mp4 20.7 MB
  • 5. Training a neural network/5. Backpropagation Intro.mp4 20.0 MB
  • 9. Backpropagation Supplementary Lectures/5. Backpropagation with Softmax Troubleshooting.mp4 19.0 MB
  • 1. Welcome/4. How to Succeed in this Course.mp4 18.3 MB
  • 4. Classifying more than 2 things at a time/7. Feedforward in Slow-Mo (part 2).mp4 17.5 MB
  • 7. TensorFlow, exercises, practice, and what to learn next/1. TensorFlow plug-and-play example.mp4 16.7 MB
  • 9. Backpropagation Supplementary Lectures/2. Why Learn the Ins and Outs of Backpropagation.mp4 16.4 MB
  • 5. Training a neural network/11. E-Commerce Course Project Training a Neural Network.mp4 16.2 MB
  • 10. Appendix/6. How to Code by Yourself (part 2).mp4 15.5 MB
  • 3. Preliminaries From Neurons to Neural Networks/2. Introduction to the E-Commerce Course Project.mp4 15.5 MB
  • 10. Appendix/2. What's the difference between neural networks and deep learning.mp4 15.5 MB
  • 5. Training a neural network/2. What do all these symbols and letters mean.mp4 15.3 MB
  • 7. TensorFlow, exercises, practice, and what to learn next/6. Deep neural networks in just 3 lines of code with Sci-Kit Learn.mp4 14.8 MB
  • 2. Review/6. Review Section Summary.mp4 14.7 MB
  • 6. Practical Machine Learning/3. Donut and XOR Revisited.mp4 14.6 MB
  • 4. Classifying more than 2 things at a time/10. Building an entire feedforward neural network in Python.mp4 14.5 MB
  • 8. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 14.1 MB
  • 10. Appendix/7. How to Succeed in this Course (Long Version).mp4 13.6 MB
  • 2. Review/1. Review Section Introduction.mp4 13.2 MB
  • 4. Classifying more than 2 things at a time/3. Interpreting the Weights of a Neural Network.mp4 13.1 MB
  • 6. Practical Machine Learning/6. Practical Considerations for Choosing Activation Functions.mp4 13.0 MB
  • 5. Training a neural network/7. Backpropagation - recursiveness.mp4 11.7 MB
  • 4. Classifying more than 2 things at a time/11. E-Commerce Course Project Pre-Processing the Data.mp4 11.7 MB
  • 5. Training a neural network/6. Backpropagation - what does the weight update depend on.mp4 10.6 MB
  • 8. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10.6 MB
  • 8. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 10.3 MB
  • 5. Training a neural network/3. What does it mean to train a neural network.mp4 10.2 MB
  • 6. Practical Machine Learning/9. Practical Issues Section Summary.mp4 10.1 MB
  • 7. TensorFlow, exercises, practice, and what to learn next/5. How to get good at deep learning + exercises.mp4 9.9 MB
  • 4. Classifying more than 2 things at a time/1. Prediction Section Introduction and Outline.mp4 9.4 MB
  • 2. Review/5. Deep Learning Readiness Test.mp4 9.0 MB
  • 4. Classifying more than 2 things at a time/2. From Logistic Regression to Neural Networks.mp4 9.0 MB
  • 10. Appendix/13. Where does this course fit into your deep learning studies (Old Version).mp4 8.9 MB
  • 5. Training a neural network/12. Training Quiz.mp4 8.7 MB
  • 7. TensorFlow, exercises, practice, and what to learn next/4. You know more than you think you know.mp4 8.6 MB
  • 10. Appendix/12. Python 2 vs Python 3.mp4 8.2 MB
  • 4. Classifying more than 2 things at a time/9. Softmax in Code.mp4 8.2 MB
  • 6. Practical Machine Learning/8. Manually Choosing Learning Rate and Regularization Penalty.mp4 8.1 MB
  • 4. Classifying more than 2 things at a time/12. E-Commerce Course Project Making Predictions.mp4 8.0 MB
  • 3. Preliminaries From Neurons to Neural Networks/1. Neural Networks with No Math.mp4 7.7 MB
  • 6. Practical Machine Learning/7. Hyperparameters and Cross-Validation.mp4 7.3 MB
  • 5. Training a neural network/9. The WRONG Way to Learn Backpropagation.mp4 7.2 MB
  • 9. Backpropagation Supplementary Lectures/4. Help with Softmax Derivative.mp4 6.6 MB
  • 1. Welcome/1. Introduction and Outline.mp4 6.4 MB
  • 7. TensorFlow, exercises, practice, and what to learn next/3. Where to go from here.mp4 6.4 MB
  • 10. Appendix/1. What is the Appendix.mp4 5.7 MB
  • 10. Appendix/10. How to Uncompress a .tar.gz file.mp4 5.7 MB
  • 4. Classifying more than 2 things at a time/13. Prediction Quizzes.mp4 5.4 MB
  • 4. Classifying more than 2 things at a time/4. Softmax.mp4 4.8 MB
  • 5. Training a neural network/1. Training Section Introduction and Outline.mp4 4.6 MB
  • 5. Training a neural network/13. Training Section Summary.mp4 4.3 MB
  • 10. Appendix/11. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4.2 MB
  • 4. Classifying more than 2 things at a time/8. Where to get the code for this course.mp4 3.1 MB
  • 8. Project Facial Expression Recognition/8. Facial Expression Recognition Project Summary.mp4 3.1 MB
  • 4. Classifying more than 2 things at a time/14. Prediction Section Summary.mp4 3.0 MB
  • 6. Practical Machine Learning/1. Practical Issues Section Introduction and Outline.mp4 2.9 MB
  • 4. Classifying more than 2 things at a time/5. Sigmoid vs. Softmax.mp4 2.5 MB
  • 6. Practical Machine Learning/5. Common nonlinearities and their derivatives.mp4 2.5 MB
  • 6. Practical Machine Learning/2. Donut and XOR Review.mp4 1.9 MB
  • 9. Backpropagation Supplementary Lectures/1. Backpropagation Supplementary Lectures Introduction.mp4 1.8 MB
  • 10. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 30.6 kB
  • 4. Classifying more than 2 things at a time/6. Feedforward in Slow-Mo (part 1).vtt 27.1 kB
  • 10. Appendix/15. What order should I take your courses in (part 2).vtt 22.8 kB
  • 10. Appendix/5. How to Code by Yourself (part 1).vtt 21.8 kB
  • 10. Appendix/3. Windows-Focused Environment Setup 2018.vtt 19.4 kB
  • 8. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.vtt 16.1 kB
  • 10. Appendix/14. What order should I take your courses in (part 1).vtt 15.5 kB
  • 9. Backpropagation Supplementary Lectures/5. Backpropagation with Softmax Troubleshooting.vtt 15.4 kB
  • 4. Classifying more than 2 things at a time/7. Feedforward in Slow-Mo (part 2).vtt 14.6 kB
  • 1. Welcome/2. Where does this course fit into your deep learning studies.vtt 14.6 kB
  • 10. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 14.3 kB
  • 10. Appendix/7. How to Succeed in this Course (Long Version).vtt 14.1 kB
  • 5. Training a neural network/2. What do all these symbols and letters mean.vtt 13.8 kB
  • 10. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt 13.5 kB
  • 3. Preliminaries From Neurons to Neural Networks/2. Introduction to the E-Commerce Course Project.vtt 13.5 kB
  • 5. Training a neural network/8. Backpropagation in code.vtt 13.5 kB
  • 10. Appendix/6. How to Code by Yourself (part 2).vtt 12.7 kB
  • 6. Practical Machine Learning/4. Neural Networks for Regression.vtt 12.6 kB
  • 9. Backpropagation Supplementary Lectures/2. Why Learn the Ins and Outs of Backpropagation.vtt 11.9 kB
  • 7. TensorFlow, exercises, practice, and what to learn next/6. Deep neural networks in just 3 lines of code with Sci-Kit Learn.vtt 11.8 kB
  • 2. Review/4. Neuron Training.vtt 11.1 kB
  • 6. Practical Machine Learning/6. Practical Considerations for Choosing Activation Functions.vtt 10.3 kB
  • 10. Appendix/2. What's the difference between neural networks and deep learning.vtt 10.0 kB
  • 4. Classifying more than 2 things at a time/3. Interpreting the Weights of a Neural Network.vtt 9.9 kB
  • 7. TensorFlow, exercises, practice, and what to learn next/2. Visualizing what a neural network has learned using TensorFlow Playground.vtt 9.6 kB
  • 5. Training a neural network/4. How to Brace Yourself to Learn Backpropagation.vtt 9.5 kB
  • 5. Training a neural network/3. What does it mean to train a neural network.vtt 9.2 kB
  • 6. Practical Machine Learning/9. Practical Issues Section Summary.vtt 9.0 kB
  • 8. Project Facial Expression Recognition/5. Facial Expression Recognition in Code (Binary Sigmoid).vtt 9.0 kB
  • 8. Project Facial Expression Recognition/7. Facial Expression Recognition in Code (ANN Softmax).vtt 8.8 kB
  • 5. Training a neural network/5. Backpropagation Intro.vtt 8.0 kB
  • 4. Classifying more than 2 things at a time/1. Prediction Section Introduction and Outline.vtt 7.9 kB
  • 2. Review/5. Deep Learning Readiness Test.vtt 7.7 kB
  • 7. TensorFlow, exercises, practice, and what to learn next/5. How to get good at deep learning + exercises.vtt 7.6 kB
  • 8. Project Facial Expression Recognition/3. The class imbalance problem.vtt 7.6 kB
  • 10. Appendix/13. Where does this course fit into your deep learning studies (Old Version).vtt 7.6 kB
  • 7. TensorFlow, exercises, practice, and what to learn next/1. TensorFlow plug-and-play example.vtt 7.4 kB
  • 2. Review/2. What does machine learning do.vtt 7.3 kB
  • 4. Classifying more than 2 things at a time/2. From Logistic Regression to Neural Networks.vtt 7.0 kB
  • 7. TensorFlow, exercises, practice, and what to learn next/4. You know more than you think you know.vtt 7.0 kB
  • 8. Project Facial Expression Recognition/6. Facial Expression Recognition in Code (Logistic Regression Softmax).vtt 7.0 kB
  • 5. Training a neural network/12. Training Quiz.vtt 6.7 kB
  • 3. Preliminaries From Neurons to Neural Networks/1. Neural Networks with No Math.vtt 6.6 kB
  • 5. Training a neural network/10. E-Commerce Course Project Training Logistic Regression with Softmax.vtt 6.6 kB
  • 6. Practical Machine Learning/7. Hyperparameters and Cross-Validation.vtt 6.4 kB
  • 1. Welcome/1. Introduction and Outline.vtt 6.3 kB
  • 8. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.vtt 6.3 kB
  • 10. Appendix/12. Python 2 vs Python 3.vtt 6.0 kB
  • 1. Welcome/3. Where to get the code.vtt 5.8 kB
  • 7. TensorFlow, exercises, practice, and what to learn next/3. Where to go from here.vtt 5.8 kB
  • 2. Review/3. Neuron Predictions.vtt 5.7 kB
  • 6. Practical Machine Learning/8. Manually Choosing Learning Rate and Regularization Penalty.vtt 5.6 kB
  • 8. Project Facial Expression Recognition/4. Utilities walkthrough.vtt 5.5 kB
  • 5. Training a neural network/9. The WRONG Way to Learn Backpropagation.vtt 5.5 kB
  • 4. Classifying more than 2 things at a time/11. E-Commerce Course Project Pre-Processing the Data.vtt 5.4 kB
  • 9. Backpropagation Supplementary Lectures/3. Gradient Descent Tutorial.vtt 5.3 kB
  • 4. Classifying more than 2 things at a time/10. Building an entire feedforward neural network in Python.vtt 5.2 kB
  • 2. Review/6. Review Section Summary.vtt 5.0 kB
  • 9. Backpropagation Supplementary Lectures/4. Help with Softmax Derivative.vtt 5.0 kB
  • 5. Training a neural network/11. E-Commerce Course Project Training a Neural Network.vtt 4.8 kB
  • 6. Practical Machine Learning/3. Donut and XOR Revisited.vtt 4.4 kB
  • 4. Classifying more than 2 things at a time/13. Prediction Quizzes.vtt 4.3 kB
  • 5. Training a neural network/1. Training Section Introduction and Outline.vtt 4.1 kB
  • 10. Appendix/10. How to Uncompress a .tar.gz file.vtt 4.0 kB
  • 4. Classifying more than 2 things at a time/4. Softmax.vtt 4.0 kB
  • 5. Training a neural network/13. Training Section Summary.vtt 3.8 kB
  • 1. Welcome/4. How to Succeed in this Course.vtt 3.8 kB
  • 4. Classifying more than 2 things at a time/9. Softmax in Code.vtt 3.7 kB
  • 4. Classifying more than 2 things at a time/12. E-Commerce Course Project Making Predictions.vtt 3.5 kB
  • 10. Appendix/1. What is the Appendix.vtt 3.5 kB
  • 10. Appendix/11. BONUS Where to get Udemy coupons and FREE deep learning material.vtt 3.4 kB
  • 5. Training a neural network/6. Backpropagation - what does the weight update depend on.vtt 3.3 kB
  • 2. Review/1. Review Section Introduction.vtt 2.7 kB
  • 4. Classifying more than 2 things at a time/14. Prediction Section Summary.vtt 2.6 kB
  • 6. Practical Machine Learning/1. Practical Issues Section Introduction and Outline.vtt 2.4 kB
  • 5. Training a neural network/7. Backpropagation - recursiveness.vtt 2.3 kB
  • 4. Classifying more than 2 things at a time/8. Where to get the code for this course.vtt 2.1 kB
  • 6. Practical Machine Learning/5. Common nonlinearities and their derivatives.vtt 1.9 kB
  • 4. Classifying more than 2 things at a time/5. Sigmoid vs. Softmax.vtt 1.8 kB
  • 8. Project Facial Expression Recognition/8. Facial Expression Recognition Project Summary.vtt 1.6 kB
  • 6. Practical Machine Learning/2. Donut and XOR Review.vtt 1.5 kB
  • 9. Backpropagation Supplementary Lectures/1. Backpropagation Supplementary Lectures Introduction.vtt 1.4 kB
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