[FreeCourseSite.com] Udemy - Complete Guide to TensorFlow for Deep Learning with Python

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[FreeCourseSite.com] Udemy - Complete Guide to TensorFlow for Deep Learning with Python

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种子哈希：cdfd3524871a25a7ee00e14ecfc1e3a0dff841ac
文件大小： 2.31G
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收录时间：2021-03-18
最近下载：2025-10-01

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文件列表

  • 1. Introduction/2.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip 314.2 MB
  • 1. Introduction/3.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip 314.2 MB
  • 6. TensorFlow Basics/8. TensorFlow Regression Example _ Part Two.mp4 60.6 MB
  • 7. Convolutional Neural Networks/13. CNN Project Exercise Solution - Part One.mp4 52.6 MB
  • 8. Recurrent Neural Networks/13. Quick Note on Word2Vec.srt 47.1 MB
  • 10. AutoEncoders/5. Stacked Autoencoder.mp4 46.1 MB
  • 5. Introduction to Neural Networks/11. Manual Neural Network Classification Task.mp4 42.5 MB
  • 9. Miscellaneous Topics/6. Tensorboard.mp4 41.9 MB
  • 10. AutoEncoders/2. Dimensionality Reduction with Linear Autoencoder.mp4 39.4 MB
  • 11. Reinforcement Learning with OpenAI Gym/8. Simple Neural Network Game.mp4 37.6 MB
  • 8. Recurrent Neural Networks/15. Word2Vec Code Along - Part One.mp4 37.3 MB
  • 8. Recurrent Neural Networks/12. Time Series Exercise Solution.mp4 36.8 MB
  • 7. Convolutional Neural Networks/7. MNIST Basic Approach Part Two.mp4 36.6 MB
  • 8. Recurrent Neural Networks/7. RNN with TensorFlow - Part One.mp4 35.8 MB
  • 8. Recurrent Neural Networks/16. Word2Vec Part Two.mp4 35.0 MB
  • 9. Miscellaneous Topics/4. Deep Nets with Tensorflow Abstractions API - Keras.mp4 35.0 MB
  • 11. Reinforcement Learning with OpenAI Gym/11. Policy Gradient Code Along Part Two.mp4 34.4 MB
  • 6. TensorFlow Basics/6. TensorFlow - A Neural Network - Part Two.mp4 34.1 MB
  • 4. Crash Course Overview/2. NumPy Crash Course.mp4 34.1 MB
  • 6. TensorFlow Basics/10. TensorFlow Classification Example - Part Two.mp4 33.5 MB
  • 3. What is Machine Learning/1. Machine Learning Overview.mp4 31.9 MB
  • 8. Recurrent Neural Networks/8. RNN with TensorFlow - Part Two.mp4 31.8 MB
  • 6. TensorFlow Basics/7. TensorFlow Regression Example - Part One.mp4 31.5 MB
  • 12. GAN - Generative Adversarial Networks/3. GAN Code Along - Part Two.mp4 30.7 MB
  • 9. Miscellaneous Topics/5. Deep Nets with Tensorflow Abstractions API - Layers.mp4 30.1 MB
  • 2. Installation and Setup/2. Installing TensorFlow and Environment Setup.mp4 29.2 MB
  • 6. TensorFlow Basics/12. TF Regression Exercise Solution Walkthrough.mp4 29.1 MB
  • 12. GAN - Generative Adversarial Networks/4. GAN Code Along - Part Three.mp4 28.9 MB
  • 5. Introduction to Neural Networks/6. TensorFlow Playground.mp4 28.5 MB
  • 7. Convolutional Neural Networks/14. CNN Project Exercise Solution - Part Two.mp4 28.3 MB
  • 7. Convolutional Neural Networks/8. CNN Theory Part One.mp4 27.9 MB
  • 7. Convolutional Neural Networks/10. CNN MNIST Code Along - Part One.mp4 27.5 MB
  • 11. Reinforcement Learning with OpenAI Gym/10. Policy Gradient Code Along Part One.mp4 27.3 MB
  • 5. Introduction to Neural Networks/10. Manual Creation of Neural Network - Part Four - Session.mp4 26.4 MB
  • 6. TensorFlow Basics/9. TensorFlow Classification Example - Part One.mp4 24.9 MB
  • 10. AutoEncoders/4. Linear Autoencoder PCA Exercise Solutions.mp4 24.0 MB
  • 6. TensorFlow Basics/14. TF Classification Exercise Solution Walkthrough.mp4 22.8 MB
  • 4. Crash Course Overview/5. SciKit Learn Preprocessing Overview.mp4 21.3 MB
  • 7. Convolutional Neural Networks/3. New Theory Topics.mp4 20.7 MB
  • 4. Crash Course Overview/4. Data Visualization Crash Course.mp4 20.5 MB
  • 12. GAN - Generative Adversarial Networks/2. GAN Code Along - Part One.mp4 20.4 MB
  • 6. TensorFlow Basics/2. TensorFlow Basic Syntax.mp4 19.9 MB
  • 9. Miscellaneous Topics/3. Deep Nets with Tensorflow Abstractions API - Estimator API.mp4 19.6 MB
  • 4. Crash Course Overview/7. Crash Course Review Exercise - Solutions.mp4 18.2 MB
  • 8. Recurrent Neural Networks/3. Manual Creation of RNN.mp4 17.5 MB
  • 8. Recurrent Neural Networks/14. Word2Vec Theory.mp4 17.4 MB
  • 1. Introduction/2. Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks ).mp4 17.2 MB
  • 9. Miscellaneous Topics/2. Deep Nets with Tensorflow Abstractions API - Part One.mp4 17.0 MB
  • 7. Convolutional Neural Networks/12. Introduction to CNN Project.mp4 16.8 MB
  • 6. TensorFlow Basics/15. Saving and Restoring Models.mp4 16.2 MB
  • 11. Reinforcement Learning with OpenAI Gym/6. Open AI Gym Observations.mp4 16.1 MB
  • 11. Reinforcement Learning with OpenAI Gym/7. OpenAI Gym Actions.mp4 15.5 MB
  • 11. Reinforcement Learning with OpenAI Gym/4. OpenAI Gym Steup.mp4 15.5 MB
  • 11. Reinforcement Learning with OpenAI Gym/3. Introduction to OpenAI Gym.mp4 14.6 MB
  • 10. AutoEncoders/1. Autoencoder Basics.mp4 14.6 MB
  • 11. Reinforcement Learning with OpenAI Gym/9. Policy Gradient Theory.mp4 14.4 MB
  • 8. Recurrent Neural Networks/11. Time Series Exercise Overview.mp4 14.3 MB
  • 12. GAN - Generative Adversarial Networks/1. Introduction to GANs.mp4 14.1 MB
  • 5. Introduction to Neural Networks/9. Manual Creation of Neural Network - Part Three - Placeholders and Variables.mp4 13.9 MB
  • 8. Recurrent Neural Networks/5. LSTM and GRU Theory.mp4 13.5 MB
  • 6. TensorFlow Basics/4. Variables and Placeholders.mp4 13.5 MB
  • 8. Recurrent Neural Networks/10. RNN with TensorFlow - Part Three.mp4 13.3 MB
  • 5. Introduction to Neural Networks/7. Manual Creation of Neural Network - Part One.mp4 13.1 MB
  • 7. Convolutional Neural Networks/6. MNIST Basic Approach Part One.mp4 12.7 MB
  • 1. Introduction/1. Introduction.mp4 12.5 MB
  • 6. TensorFlow Basics/5. TensorFlow - A Neural Network - Part One.mp4 12.2 MB
  • 5. Introduction to Neural Networks/8. Manual Creation of Neural Network - Part Two - Operations.mp4 12.0 MB
  • 8. Recurrent Neural Networks/2. RNN Theory.mp4 10.8 MB
  • 11. Reinforcement Learning with OpenAI Gym/5. Open AI Gym Env Basics.mp4 10.5 MB
  • 7. Convolutional Neural Networks/11. CNN MNIST Code Along - Part Two.mp4 10.1 MB
  • 4. Crash Course Overview/3. Pandas Crash Course.mp4 9.5 MB
  • 6. TensorFlow Basics/13. TF Classification Exercise.mp4 9.4 MB
  • 5. Introduction to Neural Networks/3. Neural Network Activation Functions.mp4 9.0 MB
  • 6. TensorFlow Basics/3. TensorFlow Graphs.mp4 9.0 MB
  • 11. Reinforcement Learning with OpenAI Gym/1. Introduction to Reinforcement Learning with OpenAI Gym.mp4 8.4 MB
  • 6. TensorFlow Basics/11. TF Regression Exercise.mp4 8.4 MB
  • 10. AutoEncoders/1.1 05-Autoencoders.zip 8.3 MB
  • 4. Crash Course Overview/6. Crash Course Review Exercise.mp4 8.0 MB
  • 5. Introduction to Neural Networks/2. Introduction to Perceptron.mp4 7.1 MB
  • 7. Convolutional Neural Networks/5. MNIST Data Overview.mp4 6.9 MB
  • 7. Convolutional Neural Networks/9. CNN Theory Part Two.mp4 6.9 MB
  • 8. Recurrent Neural Networks/6. Introduction to RNN with TensorFlow API.mp4 6.6 MB
  • 10. AutoEncoders/3. Linear Autoencoder PCA Exercise Overview.mp4 6.5 MB
  • 8. Recurrent Neural Networks/4. Vanishing Gradients.mp4 6.3 MB
  • 8. Recurrent Neural Networks/13. Quick Note on Word2Vec.mp4 6.3 MB
  • 5. Introduction to Neural Networks/4. Cost Functions.mp4 5.2 MB
  • 5. Introduction to Neural Networks/5. Gradient Descent Backpropagation.mp4 4.8 MB
  • 7. Convolutional Neural Networks/2. Review of Neural Networks.mp4 3.6 MB
  • 4. Crash Course Overview/1. Crash Course Section Introduction.mp4 2.3 MB
  • 6. TensorFlow Basics/1. Introduction to TensorFlow.mp4 2.1 MB
  • 5. Introduction to Neural Networks/1. Introduction to Neural Networks.mp4 1.7 MB
  • 8. Recurrent Neural Networks/1. Introduction to RNN Section.mp4 1.6 MB
  • 7. Convolutional Neural Networks/1. Introduction to Convolutional Neural Network Section.mp4 1.2 MB
  • 9. Miscellaneous Topics/1.1 Miscellaneous-Topics.zip 75.8 kB
  • 6. TensorFlow Basics/8. TensorFlow Regression Example _ Part Two.srt 33.5 kB
  • 6. TensorFlow Basics/7. TensorFlow Regression Example - Part One.srt 29.5 kB
  • 6. TensorFlow Basics/6. TensorFlow - A Neural Network - Part Two.srt 29.5 kB
  • 10. AutoEncoders/5. Stacked Autoencoder.srt 28.9 kB
  • 8. Recurrent Neural Networks/7. RNN with TensorFlow - Part One.srt 28.2 kB
  • 7. Convolutional Neural Networks/8. CNN Theory Part One.srt 27.9 kB
  • 3. What is Machine Learning/1. Machine Learning Overview.srt 27.2 kB
  • 8. Recurrent Neural Networks/8. RNN with TensorFlow - Part Two.srt 26.6 kB
  • 9. Miscellaneous Topics/6. Tensorboard.srt 26.3 kB
  • 10. AutoEncoders/2. Dimensionality Reduction with Linear Autoencoder.srt 25.7 kB
  • 8. Recurrent Neural Networks/15. Word2Vec Code Along - Part One.srt 25.5 kB
  • 8. Recurrent Neural Networks/12. Time Series Exercise Solution.srt 25.1 kB
  • 5. Introduction to Neural Networks/11. Manual Neural Network Classification Task.srt 24.7 kB
  • 7. Convolutional Neural Networks/7. MNIST Basic Approach Part Two.srt 24.4 kB
  • 11. Reinforcement Learning with OpenAI Gym/8. Simple Neural Network Game.srt 24.1 kB
  • 7. Convolutional Neural Networks/10. CNN MNIST Code Along - Part One.srt 24.1 kB
  • 4. Crash Course Overview/2. NumPy Crash Course.srt 23.9 kB
  • 7. Convolutional Neural Networks/3. New Theory Topics.srt 23.0 kB
  • 7. Convolutional Neural Networks/13. CNN Project Exercise Solution - Part One.srt 22.9 kB
  • 6. TensorFlow Basics/2. TensorFlow Basic Syntax.srt 20.3 kB
  • 6. TensorFlow Basics/9. TensorFlow Classification Example - Part One.srt 20.2 kB
  • 2. Installation and Setup/2. Installing TensorFlow and Environment Setup.srt 20.1 kB
  • 9. Miscellaneous Topics/4. Deep Nets with Tensorflow Abstractions API - Keras.srt 18.7 kB
  • 8. Recurrent Neural Networks/14. Word2Vec Theory.srt 18.6 kB
  • 6. TensorFlow Basics/12. TF Regression Exercise Solution Walkthrough.srt 17.6 kB
  • 6. TensorFlow Basics/10. TensorFlow Classification Example - Part Two.srt 17.3 kB
  • 11. Reinforcement Learning with OpenAI Gym/11. Policy Gradient Code Along Part Two.srt 17.2 kB
  • 8. Recurrent Neural Networks/16. Word2Vec Part Two.srt 17.2 kB
  • 6. TensorFlow Basics/14. TF Classification Exercise Solution Walkthrough.srt 17.2 kB
  • 1. Introduction/2. Course Overview -- PLEASE DON'T SKIP THIS LECTURE! Thanks ).srt 16.9 kB
  • 11. Reinforcement Learning with OpenAI Gym/10. Policy Gradient Code Along Part One.srt 16.9 kB
  • 7. Convolutional Neural Networks/14. CNN Project Exercise Solution - Part Two.srt 16.9 kB
  • 12. GAN - Generative Adversarial Networks/4. GAN Code Along - Part Three.srt 16.5 kB
  • 12. GAN - Generative Adversarial Networks/3. GAN Code Along - Part Two.srt 16.5 kB
  • 8. Recurrent Neural Networks/3. Manual Creation of RNN.srt 16.4 kB
  • 5. Introduction to Neural Networks/6. TensorFlow Playground.srt 15.7 kB
  • 9. Miscellaneous Topics/5. Deep Nets with Tensorflow Abstractions API - Layers.srt 15.6 kB
  • 8. Recurrent Neural Networks/5. LSTM and GRU Theory.srt 14.8 kB
  • 4. Crash Course Overview/5. SciKit Learn Preprocessing Overview.srt 14.0 kB
  • 5. Introduction to Neural Networks/10. Manual Creation of Neural Network - Part Four - Session.srt 13.7 kB
  • 11. Reinforcement Learning with OpenAI Gym/6. Open AI Gym Observations.srt 13.7 kB
  • 12. GAN - Generative Adversarial Networks/2. GAN Code Along - Part One.srt 13.5 kB
  • 10. AutoEncoders/1. Autoencoder Basics.srt 13.2 kB
  • 7. Convolutional Neural Networks/6. MNIST Basic Approach Part One.srt 13.1 kB
  • 11. Reinforcement Learning with OpenAI Gym/7. OpenAI Gym Actions.srt 13.1 kB
  • 5. Introduction to Neural Networks/9. Manual Creation of Neural Network - Part Three - Placeholders and Variables.srt 12.9 kB
  • 8. Recurrent Neural Networks/2. RNN Theory.srt 12.3 kB
  • 11. Reinforcement Learning with OpenAI Gym/9. Policy Gradient Theory.srt 12.2 kB
  • 11. Reinforcement Learning with OpenAI Gym/4. OpenAI Gym Steup.srt 12.1 kB
  • 8. Recurrent Neural Networks/11. Time Series Exercise Overview.srt 12.0 kB
  • 5. Introduction to Neural Networks/8. Manual Creation of Neural Network - Part Two - Operations.srt 11.8 kB
  • 4. Crash Course Overview/4. Data Visualization Crash Course.srt 11.7 kB
  • 10. AutoEncoders/4. Linear Autoencoder PCA Exercise Solutions.srt 11.5 kB
  • 6. TensorFlow Basics/5. TensorFlow - A Neural Network - Part One.srt 11.3 kB
  • 12. GAN - Generative Adversarial Networks/1. Introduction to GANs.srt 11.2 kB
  • 9. Miscellaneous Topics/3. Deep Nets with Tensorflow Abstractions API - Estimator API.srt 11.1 kB
  • 9. Miscellaneous Topics/2. Deep Nets with Tensorflow Abstractions API - Part One.srt 11.1 kB
  • 8. Recurrent Neural Networks/10. RNN with TensorFlow - Part Three.srt 10.9 kB
  • 11. Reinforcement Learning with OpenAI Gym/1.1 06-Reinforcement-Learning-OpenAI.zip 10.8 kB
  • 6. TensorFlow Basics/15. Saving and Restoring Models.srt 10.3 kB
  • 7. Convolutional Neural Networks/12. Introduction to CNN Project.srt 10.2 kB
  • 5. Introduction to Neural Networks/3. Neural Network Activation Functions.srt 9.7 kB
  • 11. Reinforcement Learning with OpenAI Gym/5. Open AI Gym Env Basics.srt 9.5 kB
  • 4. Crash Course Overview/7. Crash Course Review Exercise - Solutions.srt 9.3 kB
  • 11. Reinforcement Learning with OpenAI Gym/3. Introduction to OpenAI Gym.srt 9.2 kB
  • 6. TensorFlow Basics/4. Variables and Placeholders.srt 9.2 kB
  • 5. Introduction to Neural Networks/7. Manual Creation of Neural Network - Part One.srt 8.9 kB
  • 6. TensorFlow Basics/3. TensorFlow Graphs.srt 8.8 kB
  • 5. Introduction to Neural Networks/2. Introduction to Perceptron.srt 8.0 kB
  • 6. TensorFlow Basics/13. TF Classification Exercise.srt 7.8 kB
  • 7. Convolutional Neural Networks/11. CNN MNIST Code Along - Part Two.srt 7.8 kB
  • 8. Recurrent Neural Networks/6. Introduction to RNN with TensorFlow API.srt 7.2 kB
  • 8. Recurrent Neural Networks/4. Vanishing Gradients.srt 6.9 kB
  • 4. Crash Course Overview/3. Pandas Crash Course.srt 6.8 kB
  • 11. Reinforcement Learning with OpenAI Gym/1. Introduction to Reinforcement Learning with OpenAI Gym.srt 6.7 kB
  • 7. Convolutional Neural Networks/9. CNN Theory Part Two.srt 6.7 kB
  • 7. Convolutional Neural Networks/5. MNIST Data Overview.srt 6.5 kB
  • 6. TensorFlow Basics/11. TF Regression Exercise.srt 5.5 kB
  • 5. Introduction to Neural Networks/5. Gradient Descent Backpropagation.srt 5.4 kB
  • 5. Introduction to Neural Networks/4. Cost Functions.srt 5.4 kB
  • 1. Introduction/1. Introduction.srt 4.5 kB
  • 7. Convolutional Neural Networks/2. Review of Neural Networks.srt 4.0 kB
  • 4. Crash Course Overview/6. Crash Course Review Exercise.srt 3.7 kB
  • 10. AutoEncoders/3. Linear Autoencoder PCA Exercise Overview.srt 2.9 kB
  • 6. TensorFlow Basics/1. Introduction to TensorFlow.srt 2.3 kB
  • 2. Installation and Setup/1. Quick Note for MacOS and Linux Users.html 2.1 kB
  • 4. Crash Course Overview/1. Crash Course Section Introduction.srt 2.0 kB
  • 8. Recurrent Neural Networks/1. Introduction to RNN Section.srt 1.8 kB
  • 5. Introduction to Neural Networks/1. Introduction to Neural Networks.srt 1.5 kB
  • 7. Convolutional Neural Networks/1. Introduction to Convolutional Neural Network Section.srt 1.3 kB
  • 11. Reinforcement Learning with OpenAI Gym/2. Extra Resources for Reinforcement Learning.html 1.3 kB
  • 8. Recurrent Neural Networks/9. Quick Note on RNN Plotting Part 3.html 1.0 kB
  • 13. BONUS/1. Bonus Lecture.html 532 Bytes
  • 1. Introduction/3. FAQ - Frequently Asked Questions.html 413 Bytes
  • 9. Miscellaneous Topics/1. Intro to Miscellaneous Topics.html 344 Bytes
  • 10. AutoEncoders/1.2 Autoencoder Slides.html 161 Bytes
  • 11. Reinforcement Learning with OpenAI Gym/1.2 Reinforcement Learning Slides.html 161 Bytes
  • 3. What is Machine Learning/1.1 ML Overview Slides.html 161 Bytes
  • 5. Introduction to Neural Networks/1.1 Introduction to NN Slides.html 161 Bytes
  • 6. TensorFlow Basics/1.1 TF Basics Slides.html 161 Bytes
  • 7. Convolutional Neural Networks/1.1 CNN Slides.html 161 Bytes
  • 8. Recurrent Neural Networks/1.1 RNN Slides.html 161 Bytes
  • 6. TensorFlow Basics/15.1 Link to notebook.html 145 Bytes
  • 0. Websites you may like/[FCS Forum].url 133 Bytes
  • 0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 1. Introduction/2.2 GET THE UPDATED YML FILE HERE.html 127 Bytes
  • 1. Introduction/3.2 GET THE UPDATED YML FILE HERE.html 127 Bytes
  • 0. Websites you may like/[CourseClub.ME].url 122 Bytes
  • 7. Convolutional Neural Networks/4. Quick note on MNIST lecture.html 121 Bytes

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