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Modern Deep Learning in Python
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[TutsNode.com] - Modern Deep Learning in Python (Size: 3.76 GB) (Files: 272)
[TutsNode.com] - Modern Deep Learning in Python
18. Setting Up Your Environment (FAQ by Student Request)
1. Windows-Focused Environment Setup 2018.mp4
1. Windows-Focused Environment Setup 2018-en_US.srt
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow-en_US.srt
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
9. GPU Speedup, Homework, and Other Misc Topics
2. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer-en_US.srt
2. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4
6. Theano vs. TensorFlow-en_US.srt
5. How to Improve your Theano and Tensorflow Skills-en_US.srt
1. Setting up a GPU Instance on Amazon Web Services-en_US.srt
3. Can Big Data be used to Speed Up Backpropagation-en_US.srt
4. Exercises and Concepts Still to be Covered-en_US.srt
1. Setting up a GPU Instance on Amazon Web Services.mp4
5. How to Improve your Theano and Tensorflow Skills.mp4
6. Theano vs. TensorFlow.mp4
3. Can Big Data be used to Speed Up Backpropagation.mp4
4. Exercises and Concepts Still to be Covered.mp4
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced-en_US.srt
4. Machine Learning and AI Prerequisite Roadmap (pt 2)-en_US.srt
3. Machine Learning and AI Prerequisite Roadmap (pt 1)-en_US.srt
1. How to Succeed in this Course (Long Version)-en_US.srt
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
1. How to Succeed in this Course (Long Version).mp4
1. Introduction and Outline
2. External URLs.txt
1. Introduction and Outline-en_US.srt
3. How to Succeed in this Course-en_US.srt
2. Where to get the Code-en_US.srt
1. Introduction and Outline.mp4
3. How to Succeed in this Course.mp4
2. Where to get the Code.mp4
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)
1. How to Code by Yourself (part 1)-en_US.srt
3. Proof that using Jupyter Notebook is the same as not using it-en_US.srt
2. How to Code by Yourself (part 2)-en_US.srt
5. Python 2 vs Python 3-en_US.srt
4. How to Uncompress a .tar.gz file-en_US.srt
3. Proof that using Jupyter Notebook is the same as not using it.mp4
1. How to Code by Yourself (part 1).mp4
2. How to Code by Yourself (part 2).mp4
5. Python 2 vs Python 3.mp4
4. How to Uncompress a .tar.gz file.mp4
3. Stochastic Gradient Descent and Mini-Batch Gradient Descent
1. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Theory)-en_US.srt
4. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Code pt 2)-en_US.srt
3. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Code pt 1)-en_US.srt
2. SGD Exercise Prompt-en_US.srt
4. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Code pt 2).mp4
1. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Theory).mp4
3. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Code pt 1).mp4
2. SGD Exercise Prompt.mp4
8. TensorFlow
3. What is a Session (And more)-en_US.srt
2. Building a neural network in TensorFlow-en_US.srt
1. TensorFlow Basics Variables, Functions, Expressions, Optimization-en_US.srt
2. Building a neural network in TensorFlow.mp4
1. TensorFlow Basics Variables, Functions, Expressions, Optimization.mp4
3. What is a Session (And more).mp4
2. Review
1. Review (pt 1) Neuron Predictions-en_US.srt
6. Review Code (pt 2)-en_US.srt
3. Review (pt 3) Artificial Neural Networks-en_US.srt
7. Review Summary-en_US.srt
2. Review (pt 2) Neuron Learning-en_US.srt
4. Review Exercise Prompt-en_US.srt
5. Review Code (pt 1)-en_US.srt
6. Review Code (pt 2).mp4
1. Review (pt 1) Neuron Predictions.mp4
3. Review (pt 3) Artificial Neural Networks.mp4
4. Review Exercise Prompt.mp4
5. Review Code (pt 1).mp4
2. Review (pt 2) Neuron Learning.mp4
7. Review Summary.mp4
4. Momentum and adaptive learning rates
6. Adam Optimization (pt 1)-en_US.srt
4. Variable and adaptive learning rates-en_US.srt
7. Adam Optimization (pt 2)-en_US.srt
1. Using Momentum to Speed Up Training-en_US.srt
2. Nesterov Momentum-en_US.srt
8. Adam in Code-en_US.srt
3. Momentum in Code-en_US.srt
9. Suggestion Box-en_US.srt
5. Constant learning rate vs. RMSProp in Code-en_US.srt
6. Adam Optimization (pt 1).mp4
7. Adam Optimization (pt 2).mp4
3. Momentum in Code.mp4
8. Adam in Code.mp4
1. Using Momentum to Speed Up Training.mp4
5. Constant learning rate vs. RMSProp in Code.mp4
4. Variable and adaptive learning rates.mp4
9. Suggestion Box.mp4
2. Nesterov Momentum.mp4
11. Project Facial Expression Recognition
5. Class-Based ANN in Theano-en_US.srt
2. Facial Expression Recognition Problem Description-en_US.srt
6. Class-Based ANN in TensorFlow-en_US.srt
3. The class imbalance problem-en_US.srt
1. Facial Expression Recognition Project Introduction-en_US.srt
4. Utilities walkthrough-en_US.srt
7. Facial Expression Recognition Project Summary-en_US.srt
6. Class-Based ANN in TensorFlow.mp4
5. Class-Based ANN in Theano.mp4
2. Facial Expression Recognition Problem Description.mp4
4. Utilities walkthrough.mp4
3. The class imbalance problem.mp4
1. Facial Expression Recognition Project Introduction.mp4
7. Facial Expression Recognition Project Summary.mp4
15. PyTorch
1. PyTorch Basics-en_US.srt
2. PyTorch Dropout-en_US.srt
3. PyTorch Batch Norm-en_US.srt
1. PyTorch Basics.mp4
3. PyTorch Batch Norm.mp4
2. PyTorch Dropout.mp4
12. Modern Regularization Techniques
2. Dropout Regularization-en_US.srt
4. Noise Injection-en_US.srt
3. Dropout Intuition-en_US.srt
1. Modern Regularization Techniques Section Introduction-en_US.srt
5. Modern Regularization Techniques Section Summary-en_US.srt
2. Dropout Regularization.mp4
4. Noise Injection.mp4
3. Dropout Intuition.mp4
1. Modern Regularization Techniques Section Introduction.mp4
5. Modern Regularization Techniques Section Summary.mp4
13. Batch Normalization
3. Batch Normalization Theory-en_US.srt
7. Batch Normalization Theano (part 2)-en_US.srt
4. Batch Normalization Tensorflow (part 1)-en_US.srt
5. Batch Normalization Tensorflow (part 2)-en_US.srt
2. Exponentially-Smoothed Averages-en_US.srt
6. Batch Normalization Theano (part 1)-en_US.srt
1. Batch Normalization Introduction-en_US.srt
8. Noise Perspective-en_US.srt
9. Batch Normalization Summary-en_US.srt
7. Batch Normalization Theano (part 2).mp4
5. Batch Normalization Tensorflow (part 2).mp4
3. Batch Normalization Theory.mp4
4. Batch Normalization Tensorflow (part 1).mp4
6. Batch Normalization Theano (part 1).mp4
2. Exponentially-Smoothed Averages.mp4
1. Batch Normalization Introduction.mp4
8. Noise Perspective.mp4
9. Batch Normalization Summary.mp4
7. Theano
3. Is Theano Dead-en_US.srt
1. Theano Basics Variables, Functions, Expressions, Optimization-en_US.srt
2. Building a neural network in Theano-en_US.srt
1. Theano Basics Variables, Functions, Expressions, Optimization.mp4
2. Building a neural network in Theano.mp4
3. Is Theano Dead.mp4
6. Weight Initialization
3. Weight Initialization-en_US.srt
2. Vanishing and Exploding Gradients-en_US.srt
1. Weight Initialization Section Introduction-en_US.srt
5. Weight Initialization Section Summary-en_US.srt
4. Local vs. Global Minima-en_US.srt
3. Weight Initialization.mp4
2. Vanishing and Exploding Gradients.mp4
4. Local vs. Global Minima.mp4
5. Weight Initialization Section Summary.mp4
1. Weight Initialization Section Introduction.mp4
17. Deep Learning Review Topics
1. What's the difference between neural networks and deep learning-en_US.srt
2. Manually Choosing Learning Rate and Regularization Penalty-en_US.srt
1. What's the difference between neural networks and deep learning.mp4
2. Manually Choosing Learning Rate and Regularization Penalty.mp4
5. Choosing Hyperparameters
3. Grid Search in Code-en_US.srt
4. Modifying Grid Search-en_US.srt
1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search-en_US.srt
5. Random Search in Code-en_US.srt
2. Sampling Logarithmically-en_US.srt
3. Grid Search in Code.mp4
5. Random Search in Code.mp4
1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search.mp4
2. Sampling Logarithmically.mp4
4. Modifying Grid Search.mp4
14. Keras
1. Keras Discussion-en_US.srt
2. Keras in Code-en_US.srt
3. Keras Functional API-en_US.srt
4. How to easily convert Keras into Tensorflow 2.0 code-en_US.srt
2. Keras in Code.mp4
3. Keras Functional API.mp4
1. Keras Discussion.mp4
4. How to easily convert Keras into Tensorflow 2.0 code.mp4
21. Appendix FAQ Finale
2. BONUS Where to get discount coupons and FREE deep learning material-en_US.srt
1. What is the Appendix-en_US.srt
2. BONUS Where to get discount coupons and FREE deep learning material.mp4
1. What is the Appendix.mp4
10. Transition to the 2nd Half of the Course
1. Transition to the 2nd Half of the Course-en_US.srt
1. Transition to the 2nd Half of the Course.mp4
16. PyTorch, CNTK, and MXNet
1. PyTorch, CNTK, and MXNet-en_US.srt
1. PyTorch, CNTK, and MXNet.mp4
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