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

Creation Time	April 28, 2024, 6:10 p.m.
Last Access Time	Oct. 25, 2024, 3:10 a.m.
File Size	1.6 GB
Keywords	Lazy Python Modern - Deep Udemy Learning in Programmer Inc
Total Requests	26
Total Files	309
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17. Appendix/4. Windows-Focused Environment Setup 2018.mp4 186.3 MB
15. PyTorch/1. PyTorch Basics.mp4 116.8 MB
17. Appendix/10. Proof that using Jupyter Notebook is the same as not using it.mp4 78.3 MB
17. Appendix/2. What's the difference between neural networks and deep learning.mp4 45.1 MB
11. Project Facial Expression Recognition/5. Class-Based ANN in Theano.mp4 44.0 MB
17. Appendix/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.9 MB
17. Appendix/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39.0 MB
14. Keras/3. Keras Functional API.mp4 38.6 MB
17. Appendix/14. What order should I take your courses in (part 2).mp4 37.6 MB
11. Project Facial Expression Recognition/6. Class-Based ANN in TensorFlow.mp4 37.4 MB
15. PyTorch/3. PyTorch Batch Norm.mp4 33.9 MB
15. PyTorch/2. PyTorch Dropout.mp4 32.7 MB
17. Appendix/13. What order should I take your courses in (part 1).mp4 29.3 MB
9. GPU Speedup, Homework, and Other Misc Topics/1. Setting up a GPU Instance on Amazon Web Services.mp4 25.7 MB
17. Appendix/7. How to Code by Yourself (part 1).mp4 24.5 MB
8. TensorFlow/2. Building a neural network in TensorFlow.mp4 23.8 MB
8. TensorFlow/3. What is a Session (And more).mp4 23.6 MB
2. Review/1. Review of Basic Concepts.mp4 23.4 MB
12. Modern Regularization Techniques/2. Dropout Regularization.mp4 22.7 MB
7. Theano/2. Building a neural network in Theano.mp4 21.8 MB
11. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 21.4 MB
7. Theano/1. Theano Basics Variables, Functions, Expressions, Optimization.mp4 19.3 MB
4. Momentum and adaptive learning rates/6. Adam Optimization.mp4 19.3 MB
4. Momentum and adaptive learning rates/4. Variable and adaptive learning rates.mp4 18.9 MB
13. Batch Normalization/3. Batch Normalization Theory.mp4 18.6 MB
7. Theano/3. Is Theano Dead.mp4 17.8 MB
8. TensorFlow/1. TensorFlow Basics Variables, Functions, Expressions, Optimization.mp4 17.1 MB
13. Batch Normalization/7. Batch Normalization Theano (part 2).mp4 16.5 MB
13. Batch Normalization/5. Batch Normalization Tensorflow (part 2).mp4 14.9 MB
17. Appendix/8. How to Code by Yourself (part 2).mp4 14.8 MB
14. Keras/2. Keras in Code.mp4 14.8 MB
4. Momentum and adaptive learning rates/3. Momentum in Code.mp4 14.4 MB
1. Introduction and Outline/1. Outline - what did you learn previously, and what will you learn in this course.mp4 14.4 MB
3. Gradient Descent Full vs Batch vs Stochastic/2. Full vs Batch vs Stochastic Gradient Descent in code.mp4 14.0 MB
4. Momentum and adaptive learning rates/7. Adam in Code.mp4 13.9 MB
5. Choosing Hyperparameters/3. Grid Search in Code.mp4 13.8 MB
6. Weight Initialization/3. Weight Initialization.mp4 13.6 MB
11. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 13.5 MB
17. Appendix/6. How to Succeed in this Course (Long Version).mp4 13.0 MB
14. Keras/1. Keras Discussion.mp4 11.2 MB
2. Review/2. Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 11.1 MB
4. Momentum and adaptive learning rates/5. Constant learning rate vs. RMSProp in Code.mp4 11.0 MB
4. Momentum and adaptive learning rates/1. Using Momentum to Speed Up Training.mp4 10.7 MB
4. Momentum and adaptive learning rates/2. Nesterov Momentum.mp4 10.6 MB
11. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10.1 MB
6. Weight Initialization/2. Vanishing and Exploding Gradients.mp4 10.0 MB
11. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 9.8 MB
10. Transition to the 2nd Half of the Course/1. Transition to the 2nd Half of the Course.mp4 9.4 MB
13. Batch Normalization/4. Batch Normalization Tensorflow (part 1).mp4 9.4 MB
9. GPU Speedup, Homework, and Other Misc Topics/5. Theano vs. TensorFlow.mp4 9.1 MB
12. Modern Regularization Techniques/4. Noise Injection.mp4 8.6 MB
5. Choosing Hyperparameters/5. Random Search in Code.mp4 7.9 MB
17. Appendix/12. Python 2 vs Python 3.mp4 7.8 MB
17. Appendix/3. Manually Choosing Learning Rate and Regularization Penalty.mp4 7.8 MB
13. Batch Normalization/6. Batch Normalization Theano (part 1).mp4 7.6 MB
13. Batch Normalization/2. Exponentially-Smoothed Averages.mp4 7.4 MB
9. GPU Speedup, Homework, and Other Misc Topics/4. How to Improve your Theano and Tensorflow Skills.mp4 7.3 MB
12. Modern Regularization Techniques/3. Dropout Intuition.mp4 6.1 MB
1. Introduction and Outline/2. Where does this course fit into your deep learning studies.mp4 6.0 MB
3. Gradient Descent Full vs Batch vs Stochastic/1. What are full, batch, and stochastic gradient descent.mp4 5.8 MB
17. Appendix/1. What is the Appendix.mp4 5.5 MB
17. Appendix/11. How to Uncompress a .tar.gz file.mp4 5.4 MB
5. Choosing Hyperparameters/2. Sampling Logarithmically.mp4 5.2 MB
9. GPU Speedup, Homework, and Other Misc Topics/2. Can Big Data be used to Speed Up Backpropagation.mp4 5.2 MB
6. Weight Initialization/4. Local vs. Global Minima.mp4 5.1 MB
5. Choosing Hyperparameters/1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search.mp4 5.1 MB
9. GPU Speedup, Homework, and Other Misc Topics/3. Exercises and Concepts Still to be Covered.mp4 4.5 MB
12. Modern Regularization Techniques/1. Modern Regularization Techniques Section Introduction.mp4 4.3 MB
12. Modern Regularization Techniques/5. Modern Regularization Techniques Section Summary.mp4 3.9 MB
13. Batch Normalization/1. Batch Normalization Introduction.mp4 3.5 MB
13. Batch Normalization/8. Noise Perspective.mp4 3.1 MB
11. Project Facial Expression Recognition/7. Facial Expression Recognition Project Summary.mp4 2.9 MB
6. Weight Initialization/5. Weight Initialization Section Summary.mp4 2.7 MB
13. Batch Normalization/9. Batch Normalization Summary.mp4 2.6 MB
5. Choosing Hyperparameters/4. Modifying Grid Search.mp4 2.2 MB
6. Weight Initialization/1. Weight Initialization Section Introduction.mp4 1.5 MB
16. PyTorch, CNTK, and MXNet/1. PyTorch, CNTK, and MXNet.mp4 1.3 MB
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title.jpg 104.3 KB
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17. Appendix/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 27.8 KB
17. Appendix/14. What order should I take your courses in (part 2).vtt 20.2 KB
17. Appendix/7. How to Code by Yourself (part 1).vtt 19.8 KB
17. Appendix/4. Windows-Focused Environment Setup 2018.vtt 17.4 KB
.pad/17341 16.9 KB
2. Review/1. Review of Basic Concepts.vtt 16.0 KB
8. TensorFlow/3. What is a Session (And more).vtt 16.0 KB
.pad/15983 15.6 KB
11. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.vtt 14.3 KB
17. Appendix/13. What order should I take your courses in (part 1).vtt 14.1 KB
11. Project Facial Expression Recognition/5. Class-Based ANN in Theano.vtt 13.4 KB
4. Momentum and adaptive learning rates/4. Variable and adaptive learning rates.vtt 13.2 KB
15. PyTorch/1. PyTorch Basics.vtt 12.9 KB
17. Appendix/6. How to Succeed in this Course (Long Version).vtt 12.9 KB
12. Modern Regularization Techniques/2. Dropout Regularization.vtt 12.7 KB
17. Appendix/5. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12.4 KB
13. Batch Normalization/3. Batch Normalization Theory.vtt 12.4 KB
17. Appendix/10. Proof that using Jupyter Notebook is the same as not using it.vtt 12.2 KB
4. Momentum and adaptive learning rates/6. Adam Optimization.vtt 11.9 KB
17. Appendix/8. How to Code by Yourself (part 2).vtt 11.6 KB
11. Project Facial Expression Recognition/6. Class-Based ANN in TensorFlow.vtt 11.5 KB
7. Theano/3. Is Theano Dead.vtt 11.3 KB
.pad/11175 10.9 KB
.pad/10580 10.3 KB
1. Introduction and Outline/1. Outline - what did you learn previously, and what will you learn in this course.vtt 9.8 KB
6. Weight Initialization/3. Weight Initialization.vtt 9.1 KB
17. Appendix/2. What's the difference between neural networks and deep learning.vtt 8.9 KB
5. Choosing Hyperparameters/3. Grid Search in Code.vtt 8.2 KB
14. Keras/1. Keras Discussion.vtt 8.0 KB
9. GPU Speedup, Homework, and Other Misc Topics/5. Theano vs. TensorFlow.vtt 7.5 KB
11. Project Facial Expression Recognition/3. The class imbalance problem.vtt 7.2 KB
7. Theano/1. Theano Basics Variables, Functions, Expressions, Optimization.vtt 7.0 KB
13. Batch Normalization/7. Batch Normalization Theano (part 2).vtt 7.0 KB
6. Weight Initialization/2. Vanishing and Exploding Gradients.vtt 7.0 KB
4. Momentum and adaptive learning rates/1. Using Momentum to Speed Up Training.vtt 6.9 KB
4. Momentum and adaptive learning rates/2. Nesterov Momentum.vtt 6.8 KB
.pad/6785 6.6 KB
14. Keras/2. Keras in Code.vtt 6.5 KB
12. Modern Regularization Techniques/4. Noise Injection.vtt 6.2 KB
4. Momentum and adaptive learning rates/7. Adam in Code.vtt 6.0 KB
13. Batch Normalization/5. Batch Normalization Tensorflow (part 2).vtt 5.9 KB
13. Batch Normalization/4. Batch Normalization Tensorflow (part 1).vtt 5.9 KB
10. Transition to the 2nd Half of the Course/1. Transition to the 2nd Half of the Course.vtt 5.8 KB
3. Gradient Descent Full vs Batch vs Stochastic/2. Full vs Batch vs Stochastic Gradient Descent in code.vtt 5.8 KB
11. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.vtt 5.7 KB
8. TensorFlow/1. TensorFlow Basics Variables, Functions, Expressions, Optimization.vtt 5.6 KB
4. Momentum and adaptive learning rates/3. Momentum in Code.vtt 5.5 KB
9. GPU Speedup, Homework, and Other Misc Topics/4. How to Improve your Theano and Tensorflow Skills.vtt 5.4 KB
8. TensorFlow/2. Building a neural network in TensorFlow.vtt 5.4 KB
17. Appendix/12. Python 2 vs Python 3.vtt 5.4 KB
11. Project Facial Expression Recognition/4. Utilities walkthrough.vtt 5.2 KB
17. Appendix/3. Manually Choosing Learning Rate and Regularization Penalty.vtt 5.0 KB
1. Introduction and Outline/2. Where does this course fit into your deep learning studies.vtt 5.0 KB
13. Batch Normalization/6. Batch Normalization Theano (part 1).vtt 4.8 KB
13. Batch Normalization/2. Exponentially-Smoothed Averages.vtt 4.8 KB
14. Keras/3. Keras Functional API.vtt 4.7 KB
5. Choosing Hyperparameters/5. Random Search in Code.vtt 4.3 KB
9. GPU Speedup, Homework, and Other Misc Topics/1. Setting up a GPU Instance on Amazon Web Services.vtt 4.2 KB
2. Review/2. Where to get the MNIST dataset and Establishing a Linear Benchmark.vtt 4.2 KB
5. Choosing Hyperparameters/1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search.vtt 4.1 KB
12. Modern Regularization Techniques/3. Dropout Intuition.vtt 4.0 KB
7. Theano/2. Building a neural network in Theano.vtt 4.0 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 3.8 KB
17. Appendix/11. How to Uncompress a .tar.gz file.vtt 3.7 KB
3. Gradient Descent Full vs Batch vs Stochastic/1. What are full, batch, and stochastic gradient descent.vtt 3.5 KB
5. Choosing Hyperparameters/2. Sampling Logarithmically.vtt 3.4 KB
17. Appendix/1. What is the Appendix.vtt 3.3 KB
6. Weight Initialization/4. Local vs. Global Minima.vtt 3.1 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 2.6 KB
15. PyTorch/2. PyTorch Dropout.vtt 2.6 KB
15. PyTorch/3. PyTorch Batch Norm.vtt 2.6 KB
12. Modern Regularization Techniques/5. Modern Regularization Techniques Section Summary.vtt 2.4 KB
13. Batch Normalization/1. Batch Normalization Introduction.vtt 2.2 KB
13. Batch Normalization/8. Noise Perspective.vtt 2.2 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 1.5 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

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

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