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Download Deep Learning Recurrent Neural Networks with Python

Deep Learning Recurrent Neural Networks with Python

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Deep Learning Recurrent Neural Networks with Python

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4.8 GB

Total Files

293

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23BAEC63E70F0826F2882A45F7ED97DC8A475FCB

/.../07 Sentiment Classification using RNN/

006 RNN Setup 2.mp4

178.0 MB

TutsNode.com.txt

0.1 KB

[TGx]Downloaded from torrentgalaxy.to .txt

0.6 KB

/09 TensorFlow/

002 TensorFlow Text Classification Example using RNN.en.srt

32.5 KB

002 TensorFlow Text Classification Example using RNN.mp4

136.7 MB

001 Introduction to TensorFlow.en.srt

12.6 KB

001 Introduction to TensorFlow.mp4

44.8 MB

/.../07 Sentiment Classification using RNN/

006 RNN Setup 2.en.srt

26.2 KB

001 Vocabulary Implementation.en.srt

10.3 KB

005 RNN Setup 1.en.srt

7.6 KB

003 Vocabulary Implementation From File.en.srt

6.8 KB

004 Vectorizer.en.srt

5.6 KB

002 Vocabulary Implementation Helpers.en.srt

5.2 KB

007 WhatNext.en.srt

4.3 KB

001 Vocabulary Implementation.mp4

76.4 MB

005 RNN Setup 1.mp4

51.5 MB

003 Vocabulary Implementation From File.mp4

43.6 MB

002 Vocabulary Implementation Helpers.mp4

37.3 MB

004 Vectorizer.mp4

27.6 MB

007 WhatNext.mp4

24.3 MB

/.../02 Applications of RNN (Motivation)/

006 When to Model RNN.en.srt

23.3 KB

003 Machine Translation.en.srt

10.0 KB

001 Human Activity Recognition.en.srt

9.6 KB

005 Stock Price Predictions.en.srt

7.8 KB

002 Image Captioning.en.srt

7.7 KB

004 Speech Recognition.en.srt

7.0 KB

007 Activity.en.srt

3.1 KB

006 When to Model RNN.mp4

101.2 MB

005 Stock Price Predictions.mp4

66.2 MB

002 Image Captioning.mp4

61.6 MB

001 Human Activity Recognition.mp4

53.5 MB

003 Machine Translation.mp4

49.2 MB

004 Speech Recognition.mp4

43.2 MB

007 Activity.mp4

15.5 MB

/.../10 Project I_ Book Writer/

003 Modling RNN Architecture.en.srt

21.2 KB

002 Data Mapping.en.srt

17.9 KB

006 Modling RNN Model Text Generation.en.srt

14.5 KB

001 Introduction.en.srt

13.4 KB

004 Modling RNN Model in TensorFlow.en.srt

12.6 KB

005 Modling RNN Model Training.en.srt

8.9 KB

007 Activity.en.srt

8.6 KB

003 Modling RNN Architecture.mp4

78.9 MB

002 Data Mapping.mp4

76.9 MB

006 Modling RNN Model Text Generation.mp4

76.1 MB

001 Introduction.mp4

56.1 MB

004 Modling RNN Model in TensorFlow.mp4

51.5 MB

005 Modling RNN Model Training.mp4

40.9 MB

007 Activity.mp4

38.9 MB

/.../01 Introduction to Course/

003 Request for Your Honest Review.en.srt

2.6 KB

004 Link to oneDrive and Github to get the Python Notebooks.html

2.4 KB

001 Introduction to Instructor and Aisciences.en.srt

14.9 KB

002 Focus of the Course.en.srt

11.4 KB

001 Introduction to Instructor and Aisciences.mp4

57.4 MB

002 Focus of the Course.mp4

34.5 MB

003 Request for Your Honest Review.mp4

30.1 MB

/.../11 Project II_ Stock Price Prediction/

004 RNN Model Training and Evaluation.en.srt

20.9 KB

003 Data Prepration.en.srt

19.8 KB

002 Data Set.en.srt

12.0 KB

001 Problem Statement.en.srt

7.6 KB

005 Activity.en.srt

7.3 KB

004 RNN Model Training and Evaluation.mp4

119.6 MB

003 Data Prepration.mp4

81.2 MB

002 Data Set.mp4

66.9 MB

005 Activity.mp4

26.6 MB

001 Problem Statement.mp4

21.9 MB

/.../03 DNN Overview/

022 DropOut EarlyStopping Hyperparameters.en.srt

17.7 KB

020 Rprop Momentum.en.srt

16.6 KB

007 Discriminative vs Generative Learning.en.srt

6.3 KB

015 Backpropagation.en.srt

14.7 KB

002 Neuron and Perceptron.en.srt

13.5 KB

013 DNN Training Parameters.en.srt

13.5 KB

017 Weigth Initialization.en.srt

12.7 KB

006 Number of Nuerons vs Number of Layers.en.srt

11.6 KB

018 Batch miniBatch Stocastic.en.srt

11.4 KB

014 Gradient Descent.en.srt

10.1 KB

003 DNN Architecture.en.srt

10.0 KB

012 Activation Function.en.srt

9.9 KB

008 Universal Approximation Therorem.en.srt

8.2 KB

005 Calculating Number of Weights of DNN.en.srt

7.8 KB

010 Decision Boundary in DNN.en.srt

7.1 KB

019 Batch Normalization.en.srt

6.9 KB

011 Bias Term.en.srt

6.6 KB

004 FeedForward FullyConnected MLP.en.srt

5.9 KB

009 Why Depth.en.srt

5.2 KB

001 Introduction to Deep Learning Module.en.srt

4.5 KB

021 Convergence Animation.en.srt

4.5 KB

016 Training DNN Animantion.en.srt

4.4 KB

020 Rprop Momentum.mp4

89.2 MB

022 DropOut EarlyStopping Hyperparameters.mp4

81.7 MB

002 Neuron and Perceptron.mp4

74.4 MB

017 Weigth Initialization.mp4

66.6 MB

015 Backpropagation.mp4

58.5 MB

018 Batch miniBatch Stocastic.mp4

56.2 MB

013 DNN Training Parameters.mp4

54.7 MB

008 Universal Approximation Therorem.mp4

51.2 MB

016 Training DNN Animantion.mp4

50.4 MB

021 Convergence Animation.mp4

50.0 MB

011 Bias Term.mp4

45.3 MB

012 Activation Function.mp4

45.1 MB

014 Gradient Descent.mp4

42.6 MB

003 DNN Architecture.mp4

42.1 MB

007 Discriminative vs Generative Learning.mp4

37.3 MB

019 Batch Normalization.mp4

35.6 MB

006 Number of Nuerons vs Number of Layers.mp4

35.1 MB

010 Decision Boundary in DNN.mp4

34.9 MB

005 Calculating Number of Weights of DNN.mp4

34.9 MB

004 FeedForward FullyConnected MLP.mp4

26.4 MB

009 Why Depth.mp4

19.0 MB

001 Introduction to Deep Learning Module.mp4

11.6 MB

/.../04 RNN Architecture/

004 Weight Sharing.en.srt

16.4 KB

006 ManyToMany Model.en.srt

13.7 KB

003 Infinite Memory Architecture.en.srt

11.8 KB

002 Fixed Length Memory Model.en.srt

10.7 KB

010 ManyToMany Different Sizes Model.en.srt

10.6 KB

013 Deep RNNs.en.srt

9.7 KB

005 Notations.en.srt

9.5 KB

007 OneToMany Model.en.srt

9.1 KB

009 Activity Many to One.en.srt

7.9 KB

001 Introduction to Module.en.srt

7.4 KB

008 ManyToOne Model.en.srt

6.3 KB

011 Activity Many to Many Nmt.en.srt

5.8 KB

012 Models Summary.en.srt

4.1 KB

004 Weight Sharing.mp4

81.3 MB

003 Infinite Memory Architecture.mp4

62.7 MB

010 ManyToMany Different Sizes Model.mp4

61.7 MB

006 ManyToMany Model.mp4

54.3 MB

002 Fixed Length Memory Model.mp4

52.1 MB

005 Notations.mp4

48.1 MB

013 Deep RNNs.mp4

42.7 MB

007 OneToMany Model.mp4

41.9 MB

009 Activity Many to One.mp4

33.9 MB

008 ManyToOne Model.mp4

31.3 MB

011 Activity Many to Many Nmt.mp4

26.4 MB

012 Models Summary.mp4

22.1 MB

001 Introduction to Module.mp4

20.8 MB

/.../06 RNN implementation/

011 Language Modeling Next Word Prediction Python 6.en.srt

15.6 KB

002 Automatic Diffrenciation Pytorch.en.srt

10.2 KB

007 Language Modeling Next Word Prediction Python 2.en.srt

8.9 KB

008 Language Modeling Next Word Prediction Python 3.en.srt

7.9 KB

006 Language Modeling Next Word Prediction Python 1.en.srt

7.8 KB

009 Language Modeling Next Word Prediction Python 4.en.srt

5.6 KB

005 Language Modeling Next Word Prediction RNN Architecture.en.srt

5.0 KB

001 Automatic Diffrenciation.en.srt

4.9 KB

010 Language Modeling Next Word Prediction Python 5.en.srt

4.8 KB

003 Language Modeling Next Word Prediction Vocabulary Index.en.srt

4.4 KB

004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.en.srt

4.0 KB

011 Language Modeling Next Word Prediction Python 6.mp4

94.6 MB

008 Language Modeling Next Word Prediction Python 3.mp4

56.6 MB

007 Language Modeling Next Word Prediction Python 2.mp4

51.7 MB

006 Language Modeling Next Word Prediction Python 1.mp4

38.1 MB

002 Automatic Diffrenciation Pytorch.mp4

35.7 MB

009 Language Modeling Next Word Prediction Python 4.mp4

34.1 MB

010 Language Modeling Next Word Prediction Python 5.mp4

26.4 MB

003 Language Modeling Next Word Prediction Vocabulary Index.mp4

21.1 MB

004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.mp4

20.5 MB

005 Language Modeling Next Word Prediction RNN Architecture.mp4

20.0 MB

001 Automatic Diffrenciation.mp4

16.3 MB

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/.../08 Vanishing Gradients in RNN/

003 GRU.en.srt

13.6 KB

008 Attention Model.en.srt

11.9 KB

002 Introduction Vanishing Gradients in RNN.en.srt

9.6 KB

005 LSTM.en.srt

9.5 KB

007 Bidirectional RNN.en.srt

8.9 KB

001 Introduction to Better RNNs Module.en.srt

8.5 KB

009 Attention Model Optional.en.srt

7.0 KB

004 GRU Optional.en.srt

7.0 KB

006 LSTM Optional.en.srt

6.7 KB

003 GRU.mp4

60.3 MB

008 Attention Model.mp4

57.3 MB

002 Introduction Vanishing Gradients in RNN.mp4

47.8 MB

007 Bidirectional RNN.mp4

44.3 MB

009 Attention Model Optional.mp4

38.7 MB

005 LSTM.mp4

38.5 MB

001 Introduction to Better RNNs Module.mp4

32.7 MB

004 GRU Optional.mp4

29.1 MB

006 LSTM Optional.mp4

27.6 MB

/.../12 Further Readings and Resourses/

001 Further Readings and Resourses 1.en.srt

12.2 KB

001 Further Readings and Resourses 1.mp4

73.7 MB

/.../05 Gradient Decsent in RNN/

008 BackPropagation Through Time.en.srt

10.7 KB

001 Introduction to Gradient Descent Module.en.srt

9.7 KB

004 Loss Function.en.srt

9.5 KB

002 Example Setup.en.srt

9.5 KB

006 Chain Rule.en.srt

8.5 KB

005 Why Gradients.en.srt

7.2 KB

007 Chain Rule in Action.en.srt

7.0 KB

003 Equations.en.srt

6.4 KB

009 Activity.en.srt

2.5 KB

008 BackPropagation Through Time.mp4

74.6 MB

004 Loss Function.mp4

44.9 MB

006 Chain Rule.mp4

44.0 MB

003 Equations.mp4

38.9 MB

007 Chain Rule in Action.mp4

38.7 MB

005 Why Gradients.mp4

34.2 MB

001 Introduction to Gradient Descent Module.mp4

33.7 MB

002 Example Setup.mp4

28.2 MB

009 Activity.mp4

9.0 MB

/.../13 Bonus Lecture/

001 THANK YOU Bonus Video.en.srt

2.7 KB

001 THANK YOU Bonus Video.mp4

31.1 MB

 

Total files 293


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