| 1. Autoencoder Basics.mp4 | 13.9 MB | ||
| 1. Autoencoder Basics.srt | 12.9 KB | ||
| 1. Bonus Lecture.html | 512 B | ||
| 1. Crash Course Section Introduction.mp4 | 2.2 MB | ||
| 1. Crash Course Section Introduction.srt | 1.9 KB | ||
| 1. Intro to Miscellaneous Topics.html | 307.2 B | ||
| 1. Introduction to Convolutional Neural Network Section.mp4 | 1.2 MB | ||
| 1. Introduction to Convolutional Neural Network Section.srt | 1.3 KB | ||
| 1. Introduction to GANs.mp4 | 13.5 MB | ||
| 1. Introduction to GANs.srt | 11 KB | ||
| 1. Introduction to Neural Networks.mp4 | 1.6 MB | ||
| 1. Introduction to Neural Networks.srt | 1.5 KB | ||
| 1. Introduction to RNN Section.mp4 | 1.6 MB | ||
| 1. Introduction to RNN Section.srt | 1.7 KB | ||
| 1. Introduction to Reinforcement Learning with OpenAI Gym.mp4 | 8 MB | ||
| 1. Introduction to Reinforcement Learning with OpenAI Gym.srt | 6.5 KB | ||
| 1. Introduction to TensorFlow.mp4 | 2 MB | ||
| 1. Introduction to TensorFlow.srt | 2.2 KB | ||
| 1. Introduction.mp4 | 12 MB | ||
| 1. Introduction.srt | 4.4 KB | ||
| 1. Machine Learning Overview.mp4 | 30.4 MB | ||
| 1. Machine Learning Overview.srt | 26.6 KB | ||
| 1. Quick Note for MacOS and Linux Users.html | 2 KB | ||
| 1.1 05-Autoencoders.zip.zip | 7.9 MB | ||
| 1.1 06-Reinforcement-Learning-OpenAI.zip.zip | 10.6 KB | ||
| 1.1 CNN Slides.html | 204.8 B | ||
| 1.1 Introduction to NN Slides.html | 204.8 B | ||
| 1.1 ML Overview Slides.html | 204.8 B | ||
| 1.1 Miscellaneous-Topics.zip.zip | 74.1 KB | ||
| 1.1 RNN Slides.html | 204.8 B | ||
| 1.1 TF Basics Slides.html | 204.8 B | ||
| 1.2 Autoencoder Slides.html | 204.8 B | ||
| 1.2 Reinforcement Learning Slides.html | 204.8 B | ||
| 10. CNN MNIST Code Along - Part One.mp4 | 26.2 MB | ||
| 10. CNN MNIST Code Along - Part One.srt | 23.5 KB | ||
| 10. Manual Creation of Neural Network - Part Four - Session.mp4 | 25.2 MB | ||
| 10. Manual Creation of Neural Network - Part Four - Session.srt | 13.4 KB | ||
| 10. Policy Gradient Code Along Part One.mp4 | 26 MB | ||
| 10. Policy Gradient Code Along Part One.srt | 16.5 KB | ||
| 10. RNN with TensorFlow - Part Three.mp4 | 12.7 MB | ||
| 10. RNN with TensorFlow - Part Three.srt | 10.6 KB | ||
| 10. TensorFlow Classification Example - Part Two.mp4 | 31.9 MB | ||
| 10. TensorFlow Classification Example - Part Two.srt | 16.9 KB | ||
| 11. CNN MNIST Code Along - Part Two.mp4 | 9.6 MB | ||
| 11. CNN MNIST Code Along - Part Two.srt | 7.6 KB | ||
| 11. Manual Neural Network Classification Task.mp4 | 40.5 MB | ||
| 11. Manual Neural Network Classification Task.srt | 24.1 KB | ||
| 11. Policy Gradient Code Along Part Two.mp4 | 32.9 MB | ||
| 11. Policy Gradient Code Along Part Two.srt | 16.8 KB | ||
| 11. TF Regression Exercise.mp4 | 8 MB | ||
| 11. TF Regression Exercise.srt | 5.3 KB | ||
| 11. Time Series Exercise Overview.mp4 | 13.6 MB | ||
| 11. Time Series Exercise Overview.srt | 11.7 KB | ||
| 12. Introduction to CNN Project.mp4 | 16.1 MB | ||
| 12. Introduction to CNN Project.srt | 10 KB | ||
| 12. TF Regression Exercise Solution Walkthrough.mp4 | 27.8 MB | ||
| 12. TF Regression Exercise Solution Walkthrough.srt | 17.2 KB | ||
| 12. Time Series Exercise Solution.mp4 | 35.1 MB | ||
| 12. Time Series Exercise Solution.srt | 24.5 KB | ||
| 13. CNN Project Exercise Solution - Part One.mp4 | 50.2 MB | ||
| 13. CNN Project Exercise Solution - Part One.srt | 22.3 KB | ||
| 13. Quick Note on Word2Vec.mp4 | 6.1 MB | ||
| 13. Quick Note on Word2Vec.srt | 4.8 KB | ||
| 13. TF Classification Exercise.mp4 | 9 MB | ||
| 13. TF Classification Exercise.srt | 7.6 KB | ||
| 14. CNN Project Exercise Solution - Part Two.mp4 | 27 MB | ||
| 14. CNN Project Exercise Solution - Part Two.srt | 16.5 KB | ||
| 14. TF Classification Exercise Solution Walkthrough.mp4 | 21.7 MB | ||
| 14. TF Classification Exercise Solution Walkthrough.srt | 16.8 KB | ||
| 14. Word2Vec Theory.mp4 | 16.6 MB | ||
| 14. Word2Vec Theory.srt | 18.2 KB | ||
| 15. Saving and Restoring Models.mp4 | 15.4 MB | ||
| 15. Saving and Restoring Models.srt | 10.1 KB | ||
| 15. Word2Vec Code Along - Part One.mp4 | 35.5 MB | ||
| 15. Word2Vec Code Along - Part One.srt | 24.9 KB | ||
| 15.1 Link to notebook.html | 102.4 B | ||
| 16. Word2Vec Part Two.mp4 | 33.4 MB | ||
| 16. Word2Vec Part Two.srt | 16.2 MB | ||
| 2. Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks ).mp4 | 16.4 MB | ||
| 2. Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks ).srt | 16.5 KB | ||
| 2. Deep Nets with Tensorflow Abstractions API - Part One.mp4 | 16.3 MB | ||
| 2. Deep Nets with Tensorflow Abstractions API - Part One.srt | 10.8 KB | ||
| 2. Dimensionality Reduction with Linear Autoencoder.mp4 | 37.6 MB | ||
| 2. Dimensionality Reduction with Linear Autoencoder.srt | 25.1 KB | ||
| 2. Extra Resources for Reinforcement Learning.html | 1.2 KB | ||
| 2. GAN Code Along - Part One.mp4 | 19.5 MB | ||
| 2. GAN Code Along - Part One.srt | 13.2 KB | ||
| 2. Installing TensorFlow and Environment Setup.mp4 | 27.8 MB | ||
| 2. Installing TensorFlow and Environment Setup.srt | 19.6 KB | ||
| 2. Introduction to Perceptron.mp4 | 6.8 MB | ||
| 2. Introduction to Perceptron.srt | 7.8 KB | ||
| 2. NumPy Crash Course.mp4 | 32.5 MB | ||
| 2. NumPy Crash Course.srt | 23.3 KB | ||
| 2. RNN Theory.mp4 | 10.3 MB | ||
| 2. RNN Theory.srt | 12 KB | ||
| 2. Review of Neural Networks.mp4 | 3.4 MB | ||
| 2. Review of Neural Networks.srt | 3.9 KB | ||
| 2. TensorFlow Basic Syntax.mp4 | 19 MB | ||
| 2. TensorFlow Basic Syntax.srt | 19.8 KB | ||
| 2.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip.zip | 299.7 MB | ||
| 3. Deep Nets with Tensorflow Abstractions API - Estimator API.mp4 | 18.7 MB | ||
| 3. Deep Nets with Tensorflow Abstractions API - Estimator API.srt | 10.8 KB | ||
| 3. FAQ - Frequently Asked Questions.html | 409.6 B | ||
| 3. GAN Code Along - Part Two.mp4 | 29.3 MB | ||
| 3. GAN Code Along - Part Two.srt | 16.1 KB | ||
| 3. Introduction to OpenAI Gym.mp4 | 13.9 MB | ||
| 3. Introduction to OpenAI Gym.srt | 9 KB | ||
| 3. Linear Autoencoder PCA Exercise Overview.mp4 | 6.2 MB | ||
| 3. Linear Autoencoder PCA Exercise Overview.srt | 2.8 KB | ||
| 3. Manual Creation of RNN.mp4 | 16.6 MB | ||
| 3. Manual Creation of RNN.srt | 16 KB | ||
| 3. Neural Network Activation Functions.mp4 | 8.6 MB | ||
| 3. Neural Network Activation Functions.srt | 9.5 KB | ||
| 3. New Theory Topics.mp4 | 19.7 MB | ||
| 3. New Theory Topics.srt | 22.4 KB | ||
| 3. Pandas Crash Course.mp4 | 9 MB | ||
| 3. Pandas Crash Course.srt | 6.7 KB | ||
| 3. TensorFlow Graphs.mp4 | 8.5 MB | ||
| 3. TensorFlow Graphs.srt | 8.6 KB | ||
| 3.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip.zip | 299.7 MB | ||
| 4. Cost Functions.mp4 | 5 MB | ||
| 4. Cost Functions.srt | 5.2 KB | ||
| 4. Data Visualization Crash Course.mp4 | 19.5 MB | ||
| 4. Data Visualization Crash Course.srt | 11.4 KB | ||
| 4. Deep Nets with Tensorflow Abstractions API - Keras.mp4 | 33.4 MB | ||
| 4. Deep Nets with Tensorflow Abstractions API - Keras.srt | 18.2 KB | ||
| 4. GAN Code Along - Part Three.mp4 | 27.6 MB | ||
| 4. GAN Code Along - Part Three.srt | 16.2 KB | ||
| 4. Linear Autoencoder PCA Exercise Solutions.mp4 | 22.9 MB | ||
| 4. Linear Autoencoder PCA Exercise Solutions.srt | 11.3 KB | ||
| 4. OpenAI Gym Steup.mp4 | 14.8 MB | ||
| 4. OpenAI Gym Steup.srt | 11.8 KB | ||
| 4. Quick note on MNIST lecture.html | 102.4 B | ||
| 4. Vanishing Gradients.mp4 | 6.1 MB | ||
| 4. Vanishing Gradients.srt | 6.7 KB | ||
| 4. Variables and Placeholders.mp4 | 12.8 MB | ||
| 4. Variables and Placeholders.srt | 9 KB | ||
| 5. Deep Nets with Tensorflow Abstractions API - Layers.mp4 | 28.7 MB | ||
| 5. Deep Nets with Tensorflow Abstractions API - Layers.srt | 15.3 KB | ||
| 5. Gradient Descent Backpropagation.mp4 | 4.6 MB | ||
| 5. Gradient Descent Backpropagation.srt | 5.3 KB | ||
| 5. LSTM and GRU Theory.mp4 | 12.9 MB | ||
| 5. LSTM and GRU Theory.srt | 14.5 KB | ||
| 5. MNIST Data Overview.mp4 | 6.6 MB | ||
| 5. MNIST Data Overview.srt | 6.6 MB | ||
| 5. Open AI Gym Env Basics.mp4 | 10 MB | ||
| 5. Open AI Gym Env Basics.srt | 9.3 KB | ||
| 5. SciKit Learn Preprocessing Overview.mp4 | 20.3 MB | ||
| 5. SciKit Learn Preprocessing Overview.srt | 13.7 KB | ||
| 5. Stacked Autoencoder.mp4 | 43.9 MB | ||
| 5. Stacked Autoencoder.srt | 28.2 KB | ||
| 5. TensorFlow - A Neural Network - Part One.mp4 | 11.6 MB | ||
| 5. TensorFlow - A Neural Network - Part One.srt | 11 KB | ||
| 6. Crash Course Review Exercise.mp4 | 7.7 MB | ||
| 6. Crash Course Review Exercise.srt | 3.6 KB | ||
| 6. Introduction to RNN with TensorFlow API.mp4 | 6.3 MB | ||
| 6. Introduction to RNN with TensorFlow API.srt | 7 KB | ||
| 6. MNIST Basic Approach Part One.mp4 | 12.1 MB | ||
| 6. MNIST Basic Approach Part One.srt | 12.8 KB | ||
| 6. Open AI Gym Observations.mp4 | 15.4 MB | ||
| 6. Open AI Gym Observations.srt | 13.4 KB | ||
| 6. TensorFlow - A Neural Network - Part Two.mp4 | 32.5 MB | ||
| 6. TensorFlow - A Neural Network - Part Two.srt | 28.8 KB | ||
| 6. TensorFlow Playground.mp4 | 27.2 MB | ||
| 6. TensorFlow Playground.srt | 15.3 KB | ||
| 6. Tensorboard.mp4 | 40 MB | ||
| 6. Tensorboard.srt | 25.7 KB | ||
| 7. Crash Course Review Exercise - Solutions.mp4 | 17.4 MB | ||
| 7. Crash Course Review Exercise - Solutions.srt | 9.1 KB | ||
| 7. MNIST Basic Approach Part Two.mp4 | 34.9 MB | ||
| 7. MNIST Basic Approach Part Two.srt | 23.8 KB | ||
| 7. Manual Creation of Neural Network - Part One.mp4 | 12.5 MB | ||
| 7. Manual Creation of Neural Network - Part One.srt | 8.7 KB | ||
| 7. OpenAI Gym Actions.mp4 | 14.8 MB | ||
| 7. OpenAI Gym Actions.srt | 12.7 KB | ||
| 7. RNN with TensorFlow - Part One.mp4 | 34.1 MB | ||
| 7. RNN with TensorFlow - Part One.srt | 27.5 KB | ||
| 7. TensorFlow Regression Example - Part One.mp4 | 30.1 MB | ||
| 7. TensorFlow Regression Example - Part One.srt | 28.8 KB | ||
| 8. CNN Theory Part One.mp4 | 26.6 MB | ||
| 8. CNN Theory Part One.srt | 27.3 KB | ||
| 8. Manual Creation of Neural Network - Part Two - Operations.mp4 | 11.4 MB | ||
| 8. Manual Creation of Neural Network - Part Two - Operations.srt | 11.5 KB | ||
| 8. RNN with TensorFlow - Part Two.mp4 | 30.3 MB | ||
| 8. RNN with TensorFlow - Part Two.srt | 26 KB | ||
| 8. Simple Neural Network Game.mp4 | 35.8 MB | ||
| 8. Simple Neural Network Game.srt | 23.6 KB | ||
| 8. TensorFlow Regression Example _ Part Two.mp4 | 57.8 MB | ||
| 8. TensorFlow Regression Example _ Part Two.srt | 32.8 KB | ||
| 9. CNN Theory Part Two.mp4 | 6.5 MB | ||
| 9. CNN Theory Part Two.srt | 6.5 KB | ||
| 9. Manual Creation of Neural Network - Part Three - Placeholders and Variables.mp4 | 13.3 MB | ||
| 9. Manual Creation of Neural Network - Part Three - Placeholders and Variables.srt | 12.6 KB | ||
| 9. Policy Gradient Theory.mp4 | 13.7 MB | ||
| 9. Policy Gradient Theory.srt | 11.9 KB | ||
| 9. Quick Note on RNN Plotting Part 3.html | 1 KB | ||
| 9. TensorFlow Classification Example - Part One.mp4 | 23.8 MB | ||
| 9. TensorFlow Classification Example - Part One.srt | 19.7 KB | ||
| Readme.txt | 921.6 B | ||
| [GigaCourse.com].url | 0 B | ||
| ▲ 200 total files | |||
Udemy - Complete Guide to TensorFlow for Deep Learning with Python
Welcome to the Complete Guide to TensorFlow for Deep Learning with Python! This course will guide you through how to use Google's TensorFlow framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google's TensorFlow framework in a way that is easy to understand. Other courses and tutorials have tended to stay away from pure tensorflow and instead use abstractions that give the user less control. Here we present a course that finally serves as a complete guide to using the TensorFlow framework as intended, while showing you the latest techniques available in deep learning!
For more Udemy Courses: https://gigacourse.com
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