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Deep Learning Recurrent Neural Networks with Python
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[TutsNode.com] - Deep Learning Recurrent Neural Networks with Python (Size: 4.46 GB) (Files: 293)
[TutsNode.com] - Deep Learning Recurrent Neural Networks with Python
07 Sentiment Classification using RNN
006 RNN Setup 2.mp4
006 RNN Setup 2.en.srt
001 Vocabulary Implementation.en.srt
005 RNN Setup 1.en.srt
003 Vocabulary Implementation From File.en.srt
004 Vectorizer.en.srt
002 Vocabulary Implementation Helpers.en.srt
007 WhatNext.en.srt
001 Vocabulary Implementation.mp4
005 RNN Setup 1.mp4
003 Vocabulary Implementation From File.mp4
002 Vocabulary Implementation Helpers.mp4
004 Vectorizer.mp4
007 WhatNext.mp4
09 TensorFlow
002 TensorFlow Text Classification Example using RNN.en.srt
002 TensorFlow Text Classification Example using RNN.mp4
001 Introduction to TensorFlow.en.srt
001 Introduction to TensorFlow.mp4
02 Applications of RNN (Motivation)
006 When to Model RNN.en.srt
003 Machine Translation.en.srt
001 Human Activity Recognition.en.srt
005 Stock Price Predictions.en.srt
002 Image Captioning.en.srt
004 Speech Recognition.en.srt
007 Activity.en.srt
006 When to Model RNN.mp4
005 Stock Price Predictions.mp4
002 Image Captioning.mp4
001 Human Activity Recognition.mp4
003 Machine Translation.mp4
004 Speech Recognition.mp4
007 Activity.mp4
10 Project I_ Book Writer
003 Modling RNN Architecture.en.srt
002 Data Mapping.en.srt
006 Modling RNN Model Text Generation.en.srt
001 Introduction.en.srt
004 Modling RNN Model in TensorFlow.en.srt
005 Modling RNN Model Training.en.srt
007 Activity.en.srt
003 Modling RNN Architecture.mp4
002 Data Mapping.mp4
006 Modling RNN Model Text Generation.mp4
001 Introduction.mp4
004 Modling RNN Model in TensorFlow.mp4
005 Modling RNN Model Training.mp4
007 Activity.mp4
01 Introduction to Course
003 Request for Your Honest Review.en.srt
004 Link to oneDrive and Github to get the Python Notebooks.html
001 Introduction to Instructor and Aisciences.en.srt
002 Focus of the Course.en.srt
001 Introduction to Instructor and Aisciences.mp4
002 Focus of the Course.mp4
003 Request for Your Honest Review.mp4
11 Project II_ Stock Price Prediction
004 RNN Model Training and Evaluation.en.srt
003 Data Prepration.en.srt
002 Data Set.en.srt
001 Problem Statement.en.srt
005 Activity.en.srt
004 RNN Model Training and Evaluation.mp4
003 Data Prepration.mp4
002 Data Set.mp4
005 Activity.mp4
001 Problem Statement.mp4
03 DNN Overview
022 DropOut EarlyStopping Hyperparameters.en.srt
020 Rprop Momentum.en.srt
007 Discriminative vs Generative Learning.en.srt
015 Backpropagation.en.srt
002 Neuron and Perceptron.en.srt
013 DNN Training Parameters.en.srt
017 Weigth Initialization.en.srt
006 Number of Nuerons vs Number of Layers.en.srt
018 Batch miniBatch Stocastic.en.srt
014 Gradient Descent.en.srt
003 DNN Architecture.en.srt
012 Activation Function.en.srt
008 Universal Approximation Therorem.en.srt
005 Calculating Number of Weights of DNN.en.srt
010 Decision Boundary in DNN.en.srt
019 Batch Normalization.en.srt
011 Bias Term.en.srt
004 FeedForward FullyConnected MLP.en.srt
009 Why Depth.en.srt
001 Introduction to Deep Learning Module.en.srt
021 Convergence Animation.en.srt
016 Training DNN Animantion.en.srt
020 Rprop Momentum.mp4
022 DropOut EarlyStopping Hyperparameters.mp4
002 Neuron and Perceptron.mp4
017 Weigth Initialization.mp4
015 Backpropagation.mp4
018 Batch miniBatch Stocastic.mp4
013 DNN Training Parameters.mp4
008 Universal Approximation Therorem.mp4
016 Training DNN Animantion.mp4
021 Convergence Animation.mp4
011 Bias Term.mp4
012 Activation Function.mp4
014 Gradient Descent.mp4
003 DNN Architecture.mp4
007 Discriminative vs Generative Learning.mp4
019 Batch Normalization.mp4
006 Number of Nuerons vs Number of Layers.mp4
010 Decision Boundary in DNN.mp4
005 Calculating Number of Weights of DNN.mp4
004 FeedForward FullyConnected MLP.mp4
009 Why Depth.mp4
001 Introduction to Deep Learning Module.mp4
04 RNN Architecture
004 Weight Sharing.en.srt
006 ManyToMany Model.en.srt
003 Infinite Memory Architecture.en.srt
002 Fixed Length Memory Model.en.srt
010 ManyToMany Different Sizes Model.en.srt
013 Deep RNNs.en.srt
005 Notations.en.srt
007 OneToMany Model.en.srt
009 Activity Many to One.en.srt
001 Introduction to Module.en.srt
008 ManyToOne Model.en.srt
011 Activity Many to Many Nmt.en.srt
012 Models Summary.en.srt
004 Weight Sharing.mp4
003 Infinite Memory Architecture.mp4
010 ManyToMany Different Sizes Model.mp4
006 ManyToMany Model.mp4
002 Fixed Length Memory Model.mp4
005 Notations.mp4
013 Deep RNNs.mp4
007 OneToMany Model.mp4
009 Activity Many to One.mp4
008 ManyToOne Model.mp4
011 Activity Many to Many Nmt.mp4
012 Models Summary.mp4
001 Introduction to Module.mp4
06 RNN implementation
011 Language Modeling Next Word Prediction Python 6.en.srt
002 Automatic Diffrenciation Pytorch.en.srt
007 Language Modeling Next Word Prediction Python 2.en.srt
008 Language Modeling Next Word Prediction Python 3.en.srt
006 Language Modeling Next Word Prediction Python 1.en.srt
009 Language Modeling Next Word Prediction Python 4.en.srt
005 Language Modeling Next Word Prediction RNN Architecture.en.srt
001 Automatic Diffrenciation.en.srt
010 Language Modeling Next Word Prediction Python 5.en.srt
003 Language Modeling Next Word Prediction Vocabulary Index.en.srt
004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.en.srt
011 Language Modeling Next Word Prediction Python 6.mp4
008 Language Modeling Next Word Prediction Python 3.mp4
007 Language Modeling Next Word Prediction Python 2.mp4
006 Language Modeling Next Word Prediction Python 1.mp4
002 Automatic Diffrenciation Pytorch.mp4
009 Language Modeling Next Word Prediction Python 4.mp4
010 Language Modeling Next Word Prediction Python 5.mp4
003 Language Modeling Next Word Prediction Vocabulary Index.mp4
004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.mp4
005 Language Modeling Next Word Prediction RNN Architecture.mp4
001 Automatic Diffrenciation.mp4
08 Vanishing Gradients in RNN
003 GRU.en.srt
008 Attention Model.en.srt
002 Introduction Vanishing Gradients in RNN.en.srt
005 LSTM.en.srt
007 Bidirectional RNN.en.srt
001 Introduction to Better RNNs Module.en.srt
009 Attention Model Optional.en.srt
004 GRU Optional.en.srt
006 LSTM Optional.en.srt
003 GRU.mp4
008 Attention Model.mp4
002 Introduction Vanishing Gradients in RNN.mp4
007 Bidirectional RNN.mp4
009 Attention Model Optional.mp4
005 LSTM.mp4
001 Introduction to Better RNNs Module.mp4
004 GRU Optional.mp4
006 LSTM Optional.mp4
12 Further Readings and Resourses
001 Further Readings and Resourses 1.en.srt
001 Further Readings and Resourses 1.mp4
05 Gradient Decsent in RNN
008 BackPropagation Through Time.en.srt
001 Introduction to Gradient Descent Module.en.srt
004 Loss Function.en.srt
002 Example Setup.en.srt
006 Chain Rule.en.srt
005 Why Gradients.en.srt
007 Chain Rule in Action.en.srt
003 Equations.en.srt
009 Activity.en.srt
008 BackPropagation Through Time.mp4
004 Loss Function.mp4
006 Chain Rule.mp4
003 Equations.mp4
007 Chain Rule in Action.mp4
005 Why Gradients.mp4
001 Introduction to Gradient Descent Module.mp4
002 Example Setup.mp4
009 Activity.mp4
13 Bonus Lecture
001 THANK YOU Bonus Video.en.srt
001 THANK YOU Bonus Video.mp4
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