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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 147.0 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB

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1. Introduction/2.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip.zip 314.2 MB
1. Introduction/3.1 FULL_TENSORFLOW_NOTES__AND_DATA.zip.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
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 35.7 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 34.5 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

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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

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【压缩文件】 [ FreeCourseWeb.com ] Udemy - CNN for Computer Vision with Keras and TensorFlow in R.zip

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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB

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1. Course Overview, Installs, and Setup/3. Course Setup and Installation.mp4 159.8 MB
13. Deployment/7. Flask Front End.mp4 156.9 MB
9. Recurrent Neural Networks - RNNs/14. Bonus - Multivariate Time Series - RNN and LSTMs.mp4 156.6 MB
9. Recurrent Neural Networks - RNNs/13. RNN Exercise - Solutions.mp4 155.3 MB
7. Basic Artificial Neural Networks - ANNs/27. Tensorboard.mp4 151.2 MB
7. Basic Artificial Neural Networks - ANNs/20. Keras Project Solutions - Exploratory Data Analysis.mp4 150.6 MB
7. Basic Artificial Neural Networks - ANNs/12. Keras Regression Code Along - Exploratory Data Analysis.mp4 143.7 MB
12. Generative Adversarial Networks/4. Creating a GAN - Part Three - Model Training.mp4 138.0 MB
9. Recurrent Neural Networks - RNNs/11. RNN on a Time Series - Part Two.mp4 137.4 MB
13. Deployment/8. Live Deployment to the Web.mp4 132.7 MB
7. Basic Artificial Neural Networks - ANNs/23. Keras Project Solutions - Categorical Data.mp4 131.1 MB
11. AutoEncoders/3. Autoencoder for Dimensionality Reduction.mp4 123.2 MB
7. Basic Artificial Neural Networks - ANNs/17. Keras Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
1. Course Overview, Installs, and Setup/3.1 FINAL_TF2_FILES.zip 104.1 MB
1. Course Overview, Installs, and Setup/4.1 FINAL_TF2_FILES.zip 104.1 MB
8. Convolutional Neural Networks - CNNs/7. CNN on MNIST - Part Two - Creating and Training the Model.mp4 103.7 MB
7. Basic Artificial Neural Networks - ANNs/21. Keras Project Solutions - Dealing with Missing Data.mp4 101.5 MB
11. AutoEncoders/4. Autoencoder for Images - Part One.mp4 98.7 MB
4. Pandas Crash Course/8. Data Input and Output.mp4 98.0 MB
5. Visualization Crash Course/3. Seaborn Basics.mp4 96.3 MB

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【压缩文件】 [ FreeCourseWeb.com ] PluralSight - Implement Time Series Analysis, Forecasting and Prediction with Tensorflow 2.0.zip

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[ FreeCourseWeb.com ] PluralSight - Implement Time Series Analysis, Forecasting and Prediction with Tensorflow 2.0.zip 378.7 MB

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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB

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[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/04 Binary Classification with Artificial Neural Networks/014 Step 2 - Binary Classification.mp4 177.1 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/02 Introduction to Artificial Neural Networks (ANNs)/005 Activation Function.mp4 164.2 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/10 Project 3_ CNN for Predicting the Bank Customer Satisfaction/037 CNN for Predicting the Bank Customer Satisfaction Part 2.mp4 149.0 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/17 Natural Language Processing/073 Text Classification Part 2.mp4 146.8 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/03 Building the Artificial Neural Networks (ANNs)/009 Step 2 - Data Preprocessing.mp4 142.2 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/17 Natural Language Processing/072 Text Classification Part 1.mp4 137.4 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/06 Building Convolutional Neural Networks (CNNs)/022 Building Convolutional Neural Network Step 3.mp4 134.8 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/15 Project 6_ Google Stock Price Prediction with RNN and LSTM/056 Google Stock Price Prediction with RNN and LSTM Part 4.mp4 124.2 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/15 Project 6_ Google Stock Price Prediction with RNN and LSTM/053 Google Stock Price Prediction with RNN and LSTM Part 1.mp4 115.5 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/02 Introduction to Artificial Neural Networks (ANNs)/004 The Neuron.mp4 107.0 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/11 Project 4_ CNN for Credit Card Fraud Detection/041 CNN for Credit Card Fraud Detection Part 2.mp4 106.6 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/17 Natural Language Processing/068 Stop Words.mp4 103.3 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/09 Project 2_ CNN for Breast Cancer Detection/033 CNN for Breast Cancer Detection Part 1.mp4 101.5 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/05 Introduction to Convolutional Neural Networks (CNNs)/018 Convolutional Neural Network Part 1.mp4 100.9 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/07 CNN for Binary Image Classification/027 CNN for Binary Image Classification Step 3.mp4 99.9 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/20 Annex 3_ Data Visualization with Matplotlib/096 Matplotlib Part 4.mp4 95.6 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/11 Project 4_ CNN for Credit Card Fraud Detection/042 CNN for Credit Card Fraud Detection Part 3.mp4 95.5 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/20 Annex 3_ Data Visualization with Matplotlib/091 Matplotlib Part 1 - Functional Method.mp4 95.0 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/17 Natural Language Processing/065 Tokenization.mp4 91.0 MB
[TutsNode.com] - TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI/11 Project 4_ CNN for Credit Card Fraud Detection/040 CNN for Credit Card Fraud Detection Part 1.mp4 89.7 MB

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lesson154.mp4 151.4 MB
lesson40.mp4 148.6 MB
lesson139.mp4 131.9 MB
lesson105.mp4 131.6 MB
lesson144.mp4 130.6 MB
lesson75.mp4 126.4 MB
lesson66.mp4 125.5 MB
lesson143.mp4 124.1 MB
lesson54.mp4 123.0 MB
lesson175.mp4 119.3 MB
lesson179.mp4 118.2 MB
lesson34.mp4 118.1 MB
lesson149.mp4 110.0 MB
lesson73.mp4 109.2 MB
lesson150.mp4 109.1 MB
lesson110.mp4 108.6 MB
lesson142.mp4 108.1 MB
lesson117.mp4 107.9 MB
lesson72.mp4 105.7 MB
lesson97.mp4 102.0 MB

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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB

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