Udemy - Modern Deep Learning in Python [Lazy Programmer Inc.]

磁力链接/BT种子名称

Udemy - Modern Deep Learning in Python [Lazy Programmer Inc.]

磁力链接/BT种子简介

种子哈希：5b8edcae8a913f5782e0ee2336208c67c78c5e7c
文件大小： 1.56G
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收录时间：2024-02-12
最近下载：2025-07-21

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文件列表

  • 17. Appendix/4. Windows-Focused Environment Setup 2018.mp4 195.4 MB
  • 15. PyTorch/1. PyTorch Basics.mp4 122.5 MB
  • 17. Appendix/10. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
  • 17. Appendix/2. What's the difference between neural networks and deep learning.mp4 47.3 MB
  • 11. Project Facial Expression Recognition/5. Class-Based ANN in Theano.mp4 46.1 MB
  • 17. Appendix/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
  • 17. Appendix/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
  • 14. Keras/3. Keras Functional API.mp4 40.5 MB
  • 17. Appendix/14. What order should I take your courses in (part 2).mp4 39.4 MB
  • 11. Project Facial Expression Recognition/6. Class-Based ANN in TensorFlow.mp4 39.2 MB
  • 15. PyTorch/3. PyTorch Batch Norm.mp4 35.5 MB
  • 15. PyTorch/2. PyTorch Dropout.mp4 34.3 MB
  • 17. Appendix/13. What order should I take your courses in (part 1).mp4 30.8 MB
  • 9. GPU Speedup, Homework, and Other Misc Topics/1. Setting up a GPU Instance on Amazon Web Services.mp4 26.9 MB
  • 17. Appendix/7. How to Code by Yourself (part 1).mp4 25.7 MB
  • 8. TensorFlow/2. Building a neural network in TensorFlow.mp4 25.0 MB
  • 8. TensorFlow/3. What is a Session (And more).mp4 24.7 MB
  • 2. Review/1. Review of Basic Concepts.mp4 24.5 MB
  • 12. Modern Regularization Techniques/2. Dropout Regularization.mp4 23.8 MB
  • 7. Theano/2. Building a neural network in Theano.mp4 22.8 MB
  • 11. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 22.5 MB
  • 7. Theano/1. Theano Basics Variables, Functions, Expressions, Optimization.mp4 20.3 MB
  • 4. Momentum and adaptive learning rates/6. Adam Optimization.mp4 20.3 MB
  • 4. Momentum and adaptive learning rates/4. Variable and adaptive learning rates.mp4 19.8 MB
  • 13. Batch Normalization/3. Batch Normalization Theory.mp4 19.5 MB
  • 7. Theano/3. Is Theano Dead.mp4 18.7 MB
  • 8. TensorFlow/1. TensorFlow Basics Variables, Functions, Expressions, Optimization.mp4 17.9 MB
  • 13. Batch Normalization/7. Batch Normalization Theano (part 2).mp4 17.3 MB
  • 13. Batch Normalization/5. Batch Normalization Tensorflow (part 2).mp4 15.6 MB
  • 17. Appendix/8. How to Code by Yourself (part 2).mp4 15.5 MB
  • 14. Keras/2. Keras in Code.mp4 15.5 MB
  • 4. Momentum and adaptive learning rates/3. Momentum in Code.mp4 15.1 MB
  • 1. Introduction and Outline/1. Outline - what did you learn previously, and what will you learn in this course.mp4 15.1 MB
  • 3. Gradient Descent Full vs Batch vs Stochastic/2. Full vs Batch vs Stochastic Gradient Descent in code.mp4 14.7 MB
  • 4. Momentum and adaptive learning rates/7. Adam in Code.mp4 14.6 MB
  • 5. Choosing Hyperparameters/3. Grid Search in Code.mp4 14.4 MB
  • 6. Weight Initialization/3. Weight Initialization.mp4 14.3 MB
  • 11. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 14.1 MB
  • 17. Appendix/6. How to Succeed in this Course (Long Version).mp4 13.6 MB
  • 14. Keras/1. Keras Discussion.mp4 11.8 MB
  • 2. Review/2. Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 11.7 MB
  • 4. Momentum and adaptive learning rates/5. Constant learning rate vs. RMSProp in Code.mp4 11.5 MB
  • 4. Momentum and adaptive learning rates/1. Using Momentum to Speed Up Training.mp4 11.2 MB
  • 4. Momentum and adaptive learning rates/2. Nesterov Momentum.mp4 11.2 MB
  • 11. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10.6 MB
  • 6. Weight Initialization/2. Vanishing and Exploding Gradients.mp4 10.5 MB
  • 11. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 10.3 MB
  • 10. Transition to the 2nd Half of the Course/1. Transition to the 2nd Half of the Course.mp4 9.9 MB
  • 13. Batch Normalization/4. Batch Normalization Tensorflow (part 1).mp4 9.9 MB
  • 9. GPU Speedup, Homework, and Other Misc Topics/5. Theano vs. TensorFlow.mp4 9.6 MB
  • 12. Modern Regularization Techniques/4. Noise Injection.mp4 9.1 MB
  • 5. Choosing Hyperparameters/5. Random Search in Code.mp4 8.3 MB
  • 17. Appendix/12. Python 2 vs Python 3.mp4 8.2 MB
  • 17. Appendix/3. Manually Choosing Learning Rate and Regularization Penalty.mp4 8.1 MB
  • 13. Batch Normalization/6. Batch Normalization Theano (part 1).mp4 8.0 MB
  • 13. Batch Normalization/2. Exponentially-Smoothed Averages.mp4 7.7 MB
  • 9. GPU Speedup, Homework, and Other Misc Topics/4. How to Improve your Theano and Tensorflow Skills.mp4 7.7 MB
  • 12. Modern Regularization Techniques/3. Dropout Intuition.mp4 6.4 MB
  • 1. Introduction and Outline/2. Where does this course fit into your deep learning studies.mp4 6.3 MB
  • 3. Gradient Descent Full vs Batch vs Stochastic/1. What are full, batch, and stochastic gradient descent.mp4 6.1 MB
  • 17. Appendix/1. What is the Appendix.mp4 5.7 MB
  • 17. Appendix/11. How to Uncompress a .tar.gz file.mp4 5.7 MB
  • 5. Choosing Hyperparameters/2. Sampling Logarithmically.mp4 5.5 MB
  • 9. GPU Speedup, Homework, and Other Misc Topics/2. Can Big Data be used to Speed Up Backpropagation.mp4 5.5 MB
  • 6. Weight Initialization/4. Local vs. Global Minima.mp4 5.4 MB
  • 5. Choosing Hyperparameters/1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search.mp4 5.3 MB
  • 9. GPU Speedup, Homework, and Other Misc Topics/3. Exercises and Concepts Still to be Covered.mp4 4.7 MB
  • 12. Modern Regularization Techniques/1. Modern Regularization Techniques Section Introduction.mp4 4.5 MB
  • 12. Modern Regularization Techniques/5. Modern Regularization Techniques Section Summary.mp4 4.1 MB
  • 13. Batch Normalization/1. Batch Normalization Introduction.mp4 3.7 MB
  • 13. Batch Normalization/8. Noise Perspective.mp4 3.3 MB
  • 11. Project Facial Expression Recognition/7. Facial Expression Recognition Project Summary.mp4 3.0 MB
  • 6. Weight Initialization/5. Weight Initialization Section Summary.mp4 2.8 MB
  • 13. Batch Normalization/9. Batch Normalization Summary.mp4 2.7 MB
  • 5. Choosing Hyperparameters/4. Modifying Grid Search.mp4 2.3 MB
  • 6. Weight Initialization/1. Weight Initialization Section Introduction.mp4 1.6 MB
  • 16. PyTorch, CNTK, and MXNet/1. PyTorch, CNTK, and MXNet.mp4 1.4 MB
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  • 17. Appendix/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28.4 kB
  • 17. Appendix/14. What order should I take your courses in (part 2).vtt 20.7 kB
  • 17. Appendix/7. How to Code by Yourself (part 1).vtt 20.3 kB
  • 17. Appendix/4. Windows-Focused Environment Setup 2018.vtt 17.8 kB
  • .pad/17341 17.3 kB
  • 2. Review/1. Review of Basic Concepts.vtt 16.4 kB
  • 8. TensorFlow/3. What is a Session (And more).vtt 16.4 kB
  • .pad/15983 16.0 kB
  • 11. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.vtt 14.7 kB
  • 17. Appendix/13. What order should I take your courses in (part 1).vtt 14.4 kB
  • 11. Project Facial Expression Recognition/5. Class-Based ANN in Theano.vtt 13.7 kB
  • 4. Momentum and adaptive learning rates/4. Variable and adaptive learning rates.vtt 13.5 kB
  • 15. PyTorch/1. PyTorch Basics.vtt 13.2 kB
  • 17. Appendix/6. How to Succeed in this Course (Long Version).vtt 13.2 kB
  • 12. Modern Regularization Techniques/2. Dropout Regularization.vtt 13.0 kB
  • 17. Appendix/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12.7 kB
  • 13. Batch Normalization/3. Batch Normalization Theory.vtt 12.7 kB
  • 17. Appendix/10. Proof that using Jupyter Notebook is the same as not using it.vtt 12.5 kB
  • 4. Momentum and adaptive learning rates/6. Adam Optimization.vtt 12.2 kB
  • 17. Appendix/8. How to Code by Yourself (part 2).vtt 11.9 kB
  • 11. Project Facial Expression Recognition/6. Class-Based ANN in TensorFlow.vtt 11.8 kB
  • 7. Theano/3. Is Theano Dead.vtt 11.6 kB
  • .pad/11175 11.2 kB
  • .pad/10580 10.6 kB
  • 1. Introduction and Outline/1. Outline - what did you learn previously, and what will you learn in this course.vtt 10.0 kB
  • 6. Weight Initialization/3. Weight Initialization.vtt 9.3 kB
  • 17. Appendix/2. What's the difference between neural networks and deep learning.vtt 9.1 kB
  • 5. Choosing Hyperparameters/3. Grid Search in Code.vtt 8.3 kB
  • 14. Keras/1. Keras Discussion.vtt 8.2 kB
  • 9. GPU Speedup, Homework, and Other Misc Topics/5. Theano vs. TensorFlow.vtt 7.7 kB
  • 11. Project Facial Expression Recognition/3. The class imbalance problem.vtt 7.3 kB
  • 7. Theano/1. Theano Basics Variables, Functions, Expressions, Optimization.vtt 7.2 kB
  • 13. Batch Normalization/7. Batch Normalization Theano (part 2).vtt 7.1 kB
  • 6. Weight Initialization/2. Vanishing and Exploding Gradients.vtt 7.1 kB
  • 4. Momentum and adaptive learning rates/1. Using Momentum to Speed Up Training.vtt 7.0 kB
  • 4. Momentum and adaptive learning rates/2. Nesterov Momentum.vtt 6.9 kB
  • .pad/6785 6.8 kB
  • 14. Keras/2. Keras in Code.vtt 6.6 kB
  • 12. Modern Regularization Techniques/4. Noise Injection.vtt 6.3 kB
  • 4. Momentum and adaptive learning rates/7. Adam in Code.vtt 6.1 kB
  • 13. Batch Normalization/5. Batch Normalization Tensorflow (part 2).vtt 6.1 kB
  • 13. Batch Normalization/4. Batch Normalization Tensorflow (part 1).vtt 6.1 kB
  • 10. Transition to the 2nd Half of the Course/1. Transition to the 2nd Half of the Course.vtt 6.0 kB
  • 3. Gradient Descent Full vs Batch vs Stochastic/2. Full vs Batch vs Stochastic Gradient Descent in code.vtt 6.0 kB
  • 11. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.vtt 5.8 kB
  • 8. TensorFlow/1. TensorFlow Basics Variables, Functions, Expressions, Optimization.vtt 5.8 kB
  • 4. Momentum and adaptive learning rates/3. Momentum in Code.vtt 5.6 kB
  • 9. GPU Speedup, Homework, and Other Misc Topics/4. How to Improve your Theano and Tensorflow Skills.vtt 5.5 kB
  • 8. TensorFlow/2. Building a neural network in TensorFlow.vtt 5.5 kB
  • 17. Appendix/12. Python 2 vs Python 3.vtt 5.5 kB
  • 11. Project Facial Expression Recognition/4. Utilities walkthrough.vtt 5.4 kB
  • 17. Appendix/3. Manually Choosing Learning Rate and Regularization Penalty.vtt 5.1 kB
  • 1. Introduction and Outline/2. Where does this course fit into your deep learning studies.vtt 5.1 kB
  • 13. Batch Normalization/6. Batch Normalization Theano (part 1).vtt 4.9 kB
  • 13. Batch Normalization/2. Exponentially-Smoothed Averages.vtt 4.9 kB
  • 14. Keras/3. Keras Functional API.vtt 4.8 kB
  • 5. Choosing Hyperparameters/5. Random Search in Code.vtt 4.4 kB
  • 9. GPU Speedup, Homework, and Other Misc Topics/1. Setting up a GPU Instance on Amazon Web Services.vtt 4.3 kB
  • 2. Review/2. Where to get the MNIST dataset and Establishing a Linear Benchmark.vtt 4.3 kB
  • 5. Choosing Hyperparameters/1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search.vtt 4.2 kB
  • 12. Modern Regularization Techniques/3. Dropout Intuition.vtt 4.1 kB
  • 7. Theano/2. Building a neural network in Theano.vtt 4.1 kB
  • 9. GPU Speedup, Homework, and Other Misc Topics/2. Can Big Data be used to Speed Up Backpropagation.vtt 3.9 kB
  • 4. Momentum and adaptive learning rates/5. Constant learning rate vs. RMSProp in Code.vtt 3.9 kB
  • 17. Appendix/11. How to Uncompress a .tar.gz file.vtt 3.8 kB
  • 3. Gradient Descent Full vs Batch vs Stochastic/1. What are full, batch, and stochastic gradient descent.vtt 3.6 kB
  • 5. Choosing Hyperparameters/2. Sampling Logarithmically.vtt 3.5 kB
  • 17. Appendix/1. What is the Appendix.vtt 3.4 kB
  • 6. Weight Initialization/4. Local vs. Global Minima.vtt 3.2 kB
  • 12. Modern Regularization Techniques/1. Modern Regularization Techniques Section Introduction.vtt 2.7 kB
  • 9. GPU Speedup, Homework, and Other Misc Topics/3. Exercises and Concepts Still to be Covered.vtt 2.7 kB
  • 15. PyTorch/2. PyTorch Dropout.vtt 2.7 kB
  • 15. PyTorch/3. PyTorch Batch Norm.vtt 2.7 kB
  • 12. Modern Regularization Techniques/5. Modern Regularization Techniques Section Summary.vtt 2.4 kB
  • 13. Batch Normalization/1. Batch Normalization Introduction.vtt 2.3 kB
  • 13. Batch Normalization/8. Noise Perspective.vtt 2.3 kB
  • 13. Batch Normalization/9. Batch Normalization Summary.vtt 1.9 kB
  • 6. Weight Initialization/5. Weight Initialization Section Summary.vtt 1.9 kB
  • 5. Choosing Hyperparameters/4. Modifying Grid Search.vtt 1.6 kB
  • 11. Project Facial Expression Recognition/7. Facial Expression Recognition Project Summary.vtt 1.5 kB
  • 6. Weight Initialization/1. Weight Initialization Section Introduction.vtt 1.1 kB
  • 16. PyTorch, CNTK, and MXNet/1. PyTorch, CNTK, and MXNet.vtt 947 Bytes

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