Modern Deep Learning in Python |
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4.0 GB |
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272 |
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1640876D6BD39FC5C464B869655790A9ED46AB55 |
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/.../18. Setting Up Your Environment (FAQ by Student Request)/ |
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323.8 MB |
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/.../9. GPU Speedup, Homework, and Other Misc Topics/ |
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2. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer-en_US.srt |
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2. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 |
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5. How to Improve your Theano and Tensorflow Skills-en_US.srt |
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1. Setting up a GPU Instance on Amazon Web Services-en_US.srt |
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3. Can Big Data be used to Speed Up Backpropagation-en_US.srt |
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/.../20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/ |
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2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced-en_US.srt |
31.4 KB |
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4. Machine Learning and AI Prerequisite Roadmap (pt 2)-en_US.srt |
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3. Machine Learning and AI Prerequisite Roadmap (pt 1)-en_US.srt |
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2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 |
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/.../1. Introduction and Outline/ |
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48.8 MB |
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/.../19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/ |
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3. Proof that using Jupyter Notebook is the same as not using it-en_US.srt |
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3. Proof that using Jupyter Notebook is the same as not using it.mp4 |
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/.../3. Stochastic Gradient Descent and Mini-Batch Gradient Descent/ |
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1. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Theory)-en_US.srt |
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4. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Code pt 2)-en_US.srt |
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3. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Code pt 1)-en_US.srt |
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4. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Code pt 2).mp4 |
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1. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Theory).mp4 |
60.4 MB |
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3. Stochastic Gradient Descent and Mini-Batch Gradient Descent (Code pt 1).mp4 |
54.5 MB |
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10.2 MB |
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/.../18. Setting Up Your Environment (FAQ by Student Request)/ |
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19.5 KB |
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2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow-en_US.srt |
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2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 |
201.4 MB |
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/8. TensorFlow/ |
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1. TensorFlow Basics Variables, Functions, Expressions, Optimization-en_US.srt |
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45.5 MB |
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1. TensorFlow Basics Variables, Functions, Expressions, Optimization.mp4 |
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32.6 MB |
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/2. Review/ |
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133.0 MB |
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/.../4. Momentum and adaptive learning rates/ |
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16.4 KB |
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57.8 MB |
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/.../11. Project Facial Expression Recognition/ |
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2. Facial Expression Recognition Problem Description-en_US.srt |
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1. Facial Expression Recognition Project Introduction-en_US.srt |
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101.8 MB |
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/15. PyTorch/ |
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/.../12. Modern Regularization Techniques/ |
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1. Modern Regularization Techniques Section Introduction-en_US.srt |
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5. Modern Regularization Techniques Section Summary-en_US.srt |
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51.1 MB |
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15.3 MB |
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1. Modern Regularization Techniques Section Introduction.mp4 |
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/.../13. Batch Normalization/ |
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/7. Theano/ |
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1. Theano Basics Variables, Functions, Expressions, Optimization-en_US.srt |
7.2 KB |
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3.8 KB |
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1. Theano Basics Variables, Functions, Expressions, Optimization.mp4 |
68.5 MB |
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52.3 MB |
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24.2 MB |
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/6. Weight Initialization/ |
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/.../17. Deep Learning Review Topics/ |
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1. What's the difference between neural networks and deep learning-en_US.srt |
10.1 KB |
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2. Manually Choosing Learning Rate and Regularization Penalty-en_US.srt |
5.4 KB |
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1. What's the difference between neural networks and deep learning.mp4 |
28.5 MB |
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2. Manually Choosing Learning Rate and Regularization Penalty.mp4 |
10.8 MB |
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/5. Choosing Hyperparameters/ |
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1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search-en_US.srt |
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71.8 MB |
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40.9 MB |
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1. Hyperparameter Optimization Cross-validation, Grid Search, and Random Search.mp4 |
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/14. Keras/ |
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4. How to easily convert Keras into Tensorflow 2.0 code-en_US.srt |
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51.6 MB |
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/.../21. Appendix FAQ Finale/ |
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2. BONUS Where to get discount coupons and FREE deep learning material-en_US.srt |
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2. BONUS Where to get discount coupons and FREE deep learning material.mp4 |
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/.../10. Transition to the 2nd Half of the Course/ |
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6.6 KB |
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13.7 MB |
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/.../16. PyTorch, CNTK, and MXNet/ |
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Total files 272 |
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