[FreeCourseSite.com] Udemy - Deep Learning Recurrent Neural Networks with Python

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[FreeCourseSite.com] Udemy - Deep Learning Recurrent Neural Networks with Python

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文件大小： 4.41G
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收录时间：2024-04-16
最近下载：2025-06-15

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文件列表

  • 07 Sentiment Classification using RNN/006 RNN Setup 2.mp4 178.0 MB
  • 09 TensorFlow/002 TensorFlow Text Classification Example using RNN.mp4 136.7 MB
  • 11 Project II_ Stock Price Prediction/004 RNN Model Training and Evaluation.mp4 119.6 MB
  • 02 Applications of RNN (Motivation)/006 When to Model RNN.mp4 101.2 MB
  • 06 RNN implementation/011 Language Modeling Next Word Prediction Python 6.mp4 94.6 MB
  • 03 DNN Overview/020 Rprop Momentum.mp4 89.2 MB
  • 03 DNN Overview/022 DropOut EarlyStopping Hyperparameters.mp4 81.7 MB
  • 04 RNN Architecture/004 Weight Sharing.mp4 81.3 MB
  • 11 Project II_ Stock Price Prediction/003 Data Prepration.mp4 81.2 MB
  • 10 Project I_ Book Writer/003 Modling RNN Architecture.mp4 78.9 MB
  • 10 Project I_ Book Writer/002 Data Mapping.mp4 76.9 MB
  • 07 Sentiment Classification using RNN/001 Vocabulary Implementation.mp4 76.4 MB
  • 10 Project I_ Book Writer/006 Modling RNN Model Text Generation.mp4 76.1 MB
  • 05 Gradient Decsent in RNN/008 BackPropagation Through Time.mp4 74.6 MB
  • 03 DNN Overview/002 Neuron and Perceptron.mp4 74.4 MB
  • 12 Further Readings and Resourses/001 Further Readings and Resourses 1.mp4 73.7 MB
  • 11 Project II_ Stock Price Prediction/002 Data Set.mp4 66.9 MB
  • 03 DNN Overview/017 Weigth Initialization.mp4 66.6 MB
  • 02 Applications of RNN (Motivation)/005 Stock Price Predictions.mp4 66.2 MB
  • 04 RNN Architecture/003 Infinite Memory Architecture.mp4 62.7 MB
  • 04 RNN Architecture/010 ManyToMany Different Sizes Model.mp4 61.7 MB
  • 02 Applications of RNN (Motivation)/002 Image Captioning.mp4 61.6 MB
  • 08 Vanishing Gradients in RNN/003 GRU.mp4 60.3 MB
  • 03 DNN Overview/015 Backpropagation.mp4 58.5 MB
  • 01 Introduction to Course/001 Introduction to Instructor and Aisciences.mp4 57.4 MB
  • 08 Vanishing Gradients in RNN/008 Attention Model.mp4 57.3 MB
  • 06 RNN implementation/008 Language Modeling Next Word Prediction Python 3.mp4 56.6 MB
  • 03 DNN Overview/018 Batch miniBatch Stocastic.mp4 56.2 MB
  • 10 Project I_ Book Writer/001 Introduction.mp4 56.1 MB
  • 03 DNN Overview/013 DNN Training Parameters.mp4 54.7 MB
  • 04 RNN Architecture/006 ManyToMany Model.mp4 54.3 MB
  • 02 Applications of RNN (Motivation)/001 Human Activity Recognition.mp4 53.5 MB
  • 04 RNN Architecture/002 Fixed Length Memory Model.mp4 52.1 MB
  • 06 RNN implementation/007 Language Modeling Next Word Prediction Python 2.mp4 51.7 MB
  • 07 Sentiment Classification using RNN/005 RNN Setup 1.mp4 51.5 MB
  • 10 Project I_ Book Writer/004 Modling RNN Model in TensorFlow.mp4 51.5 MB
  • 03 DNN Overview/008 Universal Approximation Therorem.mp4 51.2 MB
  • 03 DNN Overview/016 Training DNN Animantion.mp4 50.4 MB
  • 03 DNN Overview/021 Convergence Animation.mp4 50.0 MB
  • 02 Applications of RNN (Motivation)/003 Machine Translation.mp4 49.2 MB
  • 04 RNN Architecture/005 Notations.mp4 48.1 MB
  • 08 Vanishing Gradients in RNN/002 Introduction Vanishing Gradients in RNN.mp4 47.8 MB
  • 03 DNN Overview/011 Bias Term.mp4 45.3 MB
  • 03 DNN Overview/012 Activation Function.mp4 45.1 MB
  • 05 Gradient Decsent in RNN/004 Loss Function.mp4 44.9 MB
  • 09 TensorFlow/001 Introduction to TensorFlow.mp4 44.8 MB
  • 08 Vanishing Gradients in RNN/007 Bidirectional RNN.mp4 44.3 MB
  • 05 Gradient Decsent in RNN/006 Chain Rule.mp4 44.0 MB
  • 07 Sentiment Classification using RNN/003 Vocabulary Implementation From File.mp4 43.6 MB
  • 02 Applications of RNN (Motivation)/004 Speech Recognition.mp4 43.2 MB
  • 04 RNN Architecture/013 Deep RNNs.mp4 42.7 MB
  • 03 DNN Overview/014 Gradient Descent.mp4 42.6 MB
  • 03 DNN Overview/003 DNN Architecture.mp4 42.1 MB
  • 04 RNN Architecture/007 OneToMany Model.mp4 41.9 MB
  • 10 Project I_ Book Writer/005 Modling RNN Model Training.mp4 40.9 MB
  • 05 Gradient Decsent in RNN/003 Equations.mp4 38.9 MB
  • 10 Project I_ Book Writer/007 Activity.mp4 38.9 MB
  • 08 Vanishing Gradients in RNN/009 Attention Model Optional.mp4 38.7 MB
  • 05 Gradient Decsent in RNN/007 Chain Rule in Action.mp4 38.7 MB
  • 08 Vanishing Gradients in RNN/005 LSTM.mp4 38.5 MB
  • 06 RNN implementation/006 Language Modeling Next Word Prediction Python 1.mp4 38.1 MB
  • 03 DNN Overview/007 Discriminative vs Generative Learning.mp4 37.3 MB
  • 07 Sentiment Classification using RNN/002 Vocabulary Implementation Helpers.mp4 37.3 MB
  • 06 RNN implementation/002 Automatic Diffrenciation Pytorch.mp4 35.7 MB
  • 03 DNN Overview/019 Batch Normalization.mp4 35.6 MB
  • 03 DNN Overview/006 Number of Nuerons vs Number of Layers.mp4 35.1 MB
  • 03 DNN Overview/010 Decision Boundary in DNN.mp4 34.9 MB
  • 03 DNN Overview/005 Calculating Number of Weights of DNN.mp4 34.9 MB
  • 01 Introduction to Course/002 Focus of the Course.mp4 34.5 MB
  • 05 Gradient Decsent in RNN/005 Why Gradients.mp4 34.2 MB
  • 06 RNN implementation/009 Language Modeling Next Word Prediction Python 4.mp4 34.1 MB
  • 04 RNN Architecture/009 Activity Many to One.mp4 33.9 MB
  • 05 Gradient Decsent in RNN/001 Introduction to Gradient Descent Module.mp4 33.7 MB
  • 08 Vanishing Gradients in RNN/001 Introduction to Better RNNs Module.mp4 32.7 MB
  • 04 RNN Architecture/008 ManyToOne Model.mp4 31.3 MB
  • 13 Bonus Lecture/001 THANK YOU Bonus Video.mp4 31.1 MB
  • 01 Introduction to Course/003 Request for Your Honest Review.mp4 30.1 MB
  • 08 Vanishing Gradients in RNN/004 GRU Optional.mp4 29.1 MB
  • 05 Gradient Decsent in RNN/002 Example Setup.mp4 28.2 MB
  • 07 Sentiment Classification using RNN/004 Vectorizer.mp4 27.6 MB
  • 08 Vanishing Gradients in RNN/006 LSTM Optional.mp4 27.6 MB
  • 11 Project II_ Stock Price Prediction/005 Activity.mp4 26.6 MB
  • 06 RNN implementation/010 Language Modeling Next Word Prediction Python 5.mp4 26.4 MB
  • 03 DNN Overview/004 FeedForward FullyConnected MLP.mp4 26.4 MB
  • 04 RNN Architecture/011 Activity Many to Many Nmt.mp4 26.4 MB
  • 07 Sentiment Classification using RNN/007 WhatNext.mp4 24.3 MB
  • 04 RNN Architecture/012 Models Summary.mp4 22.1 MB
  • 11 Project II_ Stock Price Prediction/001 Problem Statement.mp4 21.9 MB
  • 06 RNN implementation/003 Language Modeling Next Word Prediction Vocabulary Index.mp4 21.1 MB
  • 04 RNN Architecture/001 Introduction to Module.mp4 20.8 MB
  • 06 RNN implementation/004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.mp4 20.5 MB
  • 06 RNN implementation/005 Language Modeling Next Word Prediction RNN Architecture.mp4 20.0 MB
  • 03 DNN Overview/009 Why Depth.mp4 19.0 MB
  • 06 RNN implementation/001 Automatic Diffrenciation.mp4 16.3 MB
  • 02 Applications of RNN (Motivation)/007 Activity.mp4 15.5 MB
  • 03 DNN Overview/001 Introduction to Deep Learning Module.mp4 11.6 MB
  • 05 Gradient Decsent in RNN/009 Activity.mp4 9.0 MB
  • 09 TensorFlow/002 TensorFlow Text Classification Example using RNN.en.srt 32.5 kB
  • 07 Sentiment Classification using RNN/006 RNN Setup 2.en.srt 26.2 kB
  • 02 Applications of RNN (Motivation)/006 When to Model RNN.en.srt 23.3 kB
  • 10 Project I_ Book Writer/003 Modling RNN Architecture.en.srt 21.2 kB
  • 11 Project II_ Stock Price Prediction/004 RNN Model Training and Evaluation.en.srt 20.9 kB
  • 11 Project II_ Stock Price Prediction/003 Data Prepration.en.srt 19.8 kB
  • 10 Project I_ Book Writer/002 Data Mapping.en.srt 17.9 kB
  • 03 DNN Overview/022 DropOut EarlyStopping Hyperparameters.en.srt 17.7 kB
  • 03 DNN Overview/020 Rprop Momentum.en.srt 16.6 kB
  • 04 RNN Architecture/004 Weight Sharing.en.srt 16.4 kB
  • 06 RNN implementation/011 Language Modeling Next Word Prediction Python 6.en.srt 15.6 kB
  • 01 Introduction to Course/001 Introduction to Instructor and Aisciences.en.srt 14.9 kB
  • 03 DNN Overview/015 Backpropagation.en.srt 14.7 kB
  • 10 Project I_ Book Writer/006 Modling RNN Model Text Generation.en.srt 14.5 kB
  • 04 RNN Architecture/006 ManyToMany Model.en.srt 13.7 kB
  • 08 Vanishing Gradients in RNN/003 GRU.en.srt 13.6 kB
  • 03 DNN Overview/002 Neuron and Perceptron.en.srt 13.5 kB
  • 03 DNN Overview/013 DNN Training Parameters.en.srt 13.5 kB
  • 10 Project I_ Book Writer/001 Introduction.en.srt 13.4 kB
  • 03 DNN Overview/017 Weigth Initialization.en.srt 12.7 kB
  • 10 Project I_ Book Writer/004 Modling RNN Model in TensorFlow.en.srt 12.6 kB
  • 09 TensorFlow/001 Introduction to TensorFlow.en.srt 12.6 kB
  • 12 Further Readings and Resourses/001 Further Readings and Resourses 1.en.srt 12.2 kB
  • 11 Project II_ Stock Price Prediction/002 Data Set.en.srt 12.0 kB
  • 08 Vanishing Gradients in RNN/008 Attention Model.en.srt 11.9 kB
  • 04 RNN Architecture/003 Infinite Memory Architecture.en.srt 11.8 kB
  • 03 DNN Overview/006 Number of Nuerons vs Number of Layers.en.srt 11.6 kB
  • 01 Introduction to Course/002 Focus of the Course.en.srt 11.4 kB
  • 03 DNN Overview/018 Batch miniBatch Stocastic.en.srt 11.4 kB
  • 05 Gradient Decsent in RNN/008 BackPropagation Through Time.en.srt 10.7 kB
  • 04 RNN Architecture/002 Fixed Length Memory Model.en.srt 10.7 kB
  • 04 RNN Architecture/010 ManyToMany Different Sizes Model.en.srt 10.6 kB
  • 07 Sentiment Classification using RNN/001 Vocabulary Implementation.en.srt 10.3 kB
  • 06 RNN implementation/002 Automatic Diffrenciation Pytorch.en.srt 10.2 kB
  • 03 DNN Overview/014 Gradient Descent.en.srt 10.1 kB
  • 02 Applications of RNN (Motivation)/003 Machine Translation.en.srt 10.0 kB
  • 03 DNN Overview/003 DNN Architecture.en.srt 10.0 kB
  • 03 DNN Overview/012 Activation Function.en.srt 9.9 kB
  • 04 RNN Architecture/013 Deep RNNs.en.srt 9.7 kB
  • 05 Gradient Decsent in RNN/001 Introduction to Gradient Descent Module.en.srt 9.7 kB
  • 08 Vanishing Gradients in RNN/002 Introduction Vanishing Gradients in RNN.en.srt 9.6 kB
  • 02 Applications of RNN (Motivation)/001 Human Activity Recognition.en.srt 9.6 kB
  • 08 Vanishing Gradients in RNN/005 LSTM.en.srt 9.5 kB
  • 04 RNN Architecture/005 Notations.en.srt 9.5 kB
  • 05 Gradient Decsent in RNN/004 Loss Function.en.srt 9.5 kB
  • 05 Gradient Decsent in RNN/002 Example Setup.en.srt 9.4 kB
  • 04 RNN Architecture/007 OneToMany Model.en.srt 9.1 kB
  • 08 Vanishing Gradients in RNN/007 Bidirectional RNN.en.srt 8.9 kB
  • 06 RNN implementation/007 Language Modeling Next Word Prediction Python 2.en.srt 8.9 kB
  • 10 Project I_ Book Writer/005 Modling RNN Model Training.en.srt 8.9 kB
  • 10 Project I_ Book Writer/007 Activity.en.srt 8.6 kB
  • 08 Vanishing Gradients in RNN/001 Introduction to Better RNNs Module.en.srt 8.5 kB
  • 05 Gradient Decsent in RNN/006 Chain Rule.en.srt 8.5 kB
  • 03 DNN Overview/008 Universal Approximation Therorem.en.srt 8.2 kB
  • 06 RNN implementation/008 Language Modeling Next Word Prediction Python 3.en.srt 7.9 kB
  • 04 RNN Architecture/009 Activity Many to One.en.srt 7.9 kB
  • 02 Applications of RNN (Motivation)/005 Stock Price Predictions.en.srt 7.8 kB
  • 03 DNN Overview/005 Calculating Number of Weights of DNN.en.srt 7.8 kB
  • 06 RNN implementation/006 Language Modeling Next Word Prediction Python 1.en.srt 7.8 kB
  • 02 Applications of RNN (Motivation)/002 Image Captioning.en.srt 7.7 kB
  • 07 Sentiment Classification using RNN/005 RNN Setup 1.en.srt 7.6 kB
  • 11 Project II_ Stock Price Prediction/001 Problem Statement.en.srt 7.6 kB
  • 04 RNN Architecture/001 Introduction to Module.en.srt 7.4 kB
  • 11 Project II_ Stock Price Prediction/005 Activity.en.srt 7.3 kB
  • 05 Gradient Decsent in RNN/005 Why Gradients.en.srt 7.2 kB
  • 03 DNN Overview/010 Decision Boundary in DNN.en.srt 7.1 kB
  • 08 Vanishing Gradients in RNN/009 Attention Model Optional.en.srt 7.0 kB
  • 08 Vanishing Gradients in RNN/004 GRU Optional.en.srt 7.0 kB
  • 02 Applications of RNN (Motivation)/004 Speech Recognition.en.srt 7.0 kB
  • 05 Gradient Decsent in RNN/007 Chain Rule in Action.en.srt 7.0 kB
  • 03 DNN Overview/019 Batch Normalization.en.srt 6.9 kB
  • 07 Sentiment Classification using RNN/003 Vocabulary Implementation From File.en.srt 6.8 kB
  • 08 Vanishing Gradients in RNN/006 LSTM Optional.en.srt 6.7 kB
  • 03 DNN Overview/011 Bias Term.en.srt 6.6 kB
  • 05 Gradient Decsent in RNN/003 Equations.en.srt 6.4 kB
  • 04 RNN Architecture/008 ManyToOne Model.en.srt 6.3 kB
  • 03 DNN Overview/007 Discriminative vs Generative Learning.en.srt 6.3 kB
  • 03 DNN Overview/004 FeedForward FullyConnected MLP.en.srt 5.9 kB
  • 04 RNN Architecture/011 Activity Many to Many Nmt.en.srt 5.8 kB
  • 06 RNN implementation/009 Language Modeling Next Word Prediction Python 4.en.srt 5.6 kB
  • 07 Sentiment Classification using RNN/004 Vectorizer.en.srt 5.6 kB
  • 03 DNN Overview/009 Why Depth.en.srt 5.2 kB
  • 07 Sentiment Classification using RNN/002 Vocabulary Implementation Helpers.en.srt 5.2 kB
  • 06 RNN implementation/005 Language Modeling Next Word Prediction RNN Architecture.en.srt 5.0 kB
  • 06 RNN implementation/001 Automatic Diffrenciation.en.srt 4.9 kB
  • 06 RNN implementation/010 Language Modeling Next Word Prediction Python 5.en.srt 4.8 kB
  • 03 DNN Overview/001 Introduction to Deep Learning Module.en.srt 4.5 kB
  • 03 DNN Overview/021 Convergence Animation.en.srt 4.5 kB
  • 03 DNN Overview/016 Training DNN Animantion.en.srt 4.4 kB
  • 06 RNN implementation/003 Language Modeling Next Word Prediction Vocabulary Index.en.srt 4.4 kB
  • 07 Sentiment Classification using RNN/007 WhatNext.en.srt 4.3 kB
  • 04 RNN Architecture/012 Models Summary.en.srt 4.1 kB
  • 06 RNN implementation/004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.en.srt 4.0 kB
  • 02 Applications of RNN (Motivation)/007 Activity.en.srt 3.1 kB
  • 13 Bonus Lecture/001 THANK YOU Bonus Video.en.srt 2.7 kB
  • 01 Introduction to Course/003 Request for Your Honest Review.en.srt 2.6 kB
  • 05 Gradient Decsent in RNN/009 Activity.en.srt 2.5 kB
  • 01 Introduction to Course/004 Link to oneDrive and Github to get the Python Notebooks.html 2.4 kB
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