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

Creation Time	April 12, 2024, 10:56 p.m.
Last Access Time	Sept. 14, 2025, 12:49 a.m.
File Size	4.4 GB
Keywords	FreeCourseSite Neural Python with Recurrent - Deep Udemy Learning com Networks
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Total Files	199
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07 Sentiment Classification using RNN/006 RNN Setup 2.mp4 169.8 MB
09 TensorFlow/002 TensorFlow Text Classification Example using RNN.mp4 130.4 MB
11 Project II_ Stock Price Prediction/004 RNN Model Training and Evaluation.mp4 114.1 MB
02 Applications of RNN (Motivation)/006 When to Model RNN.mp4 96.5 MB
06 RNN implementation/011 Language Modeling Next Word Prediction Python 6.mp4 90.3 MB
03 DNN Overview/020 Rprop Momentum.mp4 85.1 MB
03 DNN Overview/022 DropOut EarlyStopping Hyperparameters.mp4 77.9 MB
04 RNN Architecture/004 Weight Sharing.mp4 77.6 MB
11 Project II_ Stock Price Prediction/003 Data Prepration.mp4 77.4 MB
10 Project I_ Book Writer/003 Modling RNN Architecture.mp4 75.2 MB
10 Project I_ Book Writer/002 Data Mapping.mp4 73.4 MB
07 Sentiment Classification using RNN/001 Vocabulary Implementation.mp4 72.9 MB
10 Project I_ Book Writer/006 Modling RNN Model Text Generation.mp4 72.5 MB
05 Gradient Decsent in RNN/008 BackPropagation Through Time.mp4 71.2 MB
03 DNN Overview/002 Neuron and Perceptron.mp4 70.9 MB
12 Further Readings and Resourses/001 Further Readings and Resourses 1.mp4 70.3 MB
11 Project II_ Stock Price Prediction/002 Data Set.mp4 63.8 MB
03 DNN Overview/017 Weigth Initialization.mp4 63.5 MB
02 Applications of RNN (Motivation)/005 Stock Price Predictions.mp4 63.2 MB
04 RNN Architecture/003 Infinite Memory Architecture.mp4 59.8 MB
04 RNN Architecture/010 ManyToMany Different Sizes Model.mp4 58.9 MB
02 Applications of RNN (Motivation)/002 Image Captioning.mp4 58.7 MB
08 Vanishing Gradients in RNN/003 GRU.mp4 57.5 MB
03 DNN Overview/015 Backpropagation.mp4 55.8 MB
01 Introduction to Course/001 Introduction to Instructor and Aisciences.mp4 54.7 MB
08 Vanishing Gradients in RNN/008 Attention Model.mp4 54.7 MB
06 RNN implementation/008 Language Modeling Next Word Prediction Python 3.mp4 54.0 MB
03 DNN Overview/018 Batch miniBatch Stocastic.mp4 53.6 MB
10 Project I_ Book Writer/001 Introduction.mp4 53.5 MB
03 DNN Overview/013 DNN Training Parameters.mp4 52.2 MB
04 RNN Architecture/006 ManyToMany Model.mp4 51.8 MB
02 Applications of RNN (Motivation)/001 Human Activity Recognition.mp4 51.0 MB
04 RNN Architecture/002 Fixed Length Memory Model.mp4 49.7 MB
06 RNN implementation/007 Language Modeling Next Word Prediction Python 2.mp4 49.3 MB
07 Sentiment Classification using RNN/005 RNN Setup 1.mp4 49.1 MB
10 Project I_ Book Writer/004 Modling RNN Model in TensorFlow.mp4 49.1 MB
03 DNN Overview/008 Universal Approximation Therorem.mp4 48.8 MB
03 DNN Overview/016 Training DNN Animantion.mp4 48.0 MB
03 DNN Overview/021 Convergence Animation.mp4 47.7 MB
02 Applications of RNN (Motivation)/003 Machine Translation.mp4 46.9 MB
04 RNN Architecture/005 Notations.mp4 45.9 MB
08 Vanishing Gradients in RNN/002 Introduction Vanishing Gradients in RNN.mp4 45.5 MB
03 DNN Overview/011 Bias Term.mp4 43.2 MB
03 DNN Overview/012 Activation Function.mp4 43.0 MB
05 Gradient Decsent in RNN/004 Loss Function.mp4 42.8 MB
09 TensorFlow/001 Introduction to TensorFlow.mp4 42.7 MB
08 Vanishing Gradients in RNN/007 Bidirectional RNN.mp4 42.2 MB
05 Gradient Decsent in RNN/006 Chain Rule.mp4 42.0 MB
07 Sentiment Classification using RNN/003 Vocabulary Implementation From File.mp4 41.6 MB
02 Applications of RNN (Motivation)/004 Speech Recognition.mp4 41.2 MB
04 RNN Architecture/013 Deep RNNs.mp4 40.7 MB
03 DNN Overview/014 Gradient Descent.mp4 40.7 MB
03 DNN Overview/003 DNN Architecture.mp4 40.2 MB
04 RNN Architecture/007 OneToMany Model.mp4 40.0 MB
10 Project I_ Book Writer/005 Modling RNN Model Training.mp4 39.0 MB
05 Gradient Decsent in RNN/003 Equations.mp4 37.1 MB
10 Project I_ Book Writer/007 Activity.mp4 37.1 MB
08 Vanishing Gradients in RNN/009 Attention Model Optional.mp4 36.9 MB
05 Gradient Decsent in RNN/007 Chain Rule in Action.mp4 36.9 MB
08 Vanishing Gradients in RNN/005 LSTM.mp4 36.7 MB
06 RNN implementation/006 Language Modeling Next Word Prediction Python 1.mp4 36.4 MB
03 DNN Overview/007 Discriminative vs Generative Learning.mp4 35.6 MB
07 Sentiment Classification using RNN/002 Vocabulary Implementation Helpers.mp4 35.5 MB
06 RNN implementation/002 Automatic Diffrenciation Pytorch.mp4 34.1 MB
03 DNN Overview/019 Batch Normalization.mp4 33.9 MB
03 DNN Overview/006 Number of Nuerons vs Number of Layers.mp4 33.5 MB
03 DNN Overview/010 Decision Boundary in DNN.mp4 33.3 MB
03 DNN Overview/005 Calculating Number of Weights of DNN.mp4 33.3 MB
01 Introduction to Course/002 Focus of the Course.mp4 32.9 MB
05 Gradient Decsent in RNN/005 Why Gradients.mp4 32.6 MB
06 RNN implementation/009 Language Modeling Next Word Prediction Python 4.mp4 32.5 MB
04 RNN Architecture/009 Activity Many to One.mp4 32.3 MB
05 Gradient Decsent in RNN/001 Introduction to Gradient Descent Module.mp4 32.2 MB
08 Vanishing Gradients in RNN/001 Introduction to Better RNNs Module.mp4 31.2 MB
04 RNN Architecture/008 ManyToOne Model.mp4 29.8 MB
13 Bonus Lecture/001 THANK YOU Bonus Video.mp4 29.7 MB
01 Introduction to Course/003 Request for Your Honest Review.mp4 28.7 MB
08 Vanishing Gradients in RNN/004 GRU Optional.mp4 27.8 MB
05 Gradient Decsent in RNN/002 Example Setup.mp4 26.9 MB
07 Sentiment Classification using RNN/004 Vectorizer.mp4 26.3 MB
08 Vanishing Gradients in RNN/006 LSTM Optional.mp4 26.3 MB
11 Project II_ Stock Price Prediction/005 Activity.mp4 25.4 MB
06 RNN implementation/010 Language Modeling Next Word Prediction Python 5.mp4 25.2 MB
03 DNN Overview/004 FeedForward FullyConnected MLP.mp4 25.2 MB
04 RNN Architecture/011 Activity Many to Many Nmt.mp4 25.1 MB
07 Sentiment Classification using RNN/007 WhatNext.mp4 23.2 MB
04 RNN Architecture/012 Models Summary.mp4 21.1 MB
11 Project II_ Stock Price Prediction/001 Problem Statement.mp4 20.9 MB
06 RNN implementation/003 Language Modeling Next Word Prediction Vocabulary Index.mp4 20.1 MB
04 RNN Architecture/001 Introduction to Module.mp4 19.9 MB
06 RNN implementation/004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.mp4 19.5 MB
06 RNN implementation/005 Language Modeling Next Word Prediction RNN Architecture.mp4 19.1 MB
03 DNN Overview/009 Why Depth.mp4 18.1 MB
06 RNN implementation/001 Automatic Diffrenciation.mp4 15.6 MB
02 Applications of RNN (Motivation)/007 Activity.mp4 14.8 MB
03 DNN Overview/001 Introduction to Deep Learning Module.mp4 11.1 MB
05 Gradient Decsent in RNN/009 Activity.mp4 8.6 MB
09 TensorFlow/002 TensorFlow Text Classification Example using RNN.en.srt 31.7 KB
07 Sentiment Classification using RNN/006 RNN Setup 2.en.srt 25.6 KB
02 Applications of RNN (Motivation)/006 When to Model RNN.en.srt 22.7 KB
10 Project I_ Book Writer/003 Modling RNN Architecture.en.srt 20.7 KB
11 Project II_ Stock Price Prediction/004 RNN Model Training and Evaluation.en.srt 20.4 KB
11 Project II_ Stock Price Prediction/003 Data Prepration.en.srt 19.4 KB
10 Project I_ Book Writer/002 Data Mapping.en.srt 17.4 KB
03 DNN Overview/022 DropOut EarlyStopping Hyperparameters.en.srt 17.3 KB
03 DNN Overview/020 Rprop Momentum.en.srt 16.2 KB
04 RNN Architecture/004 Weight Sharing.en.srt 16.0 KB
06 RNN implementation/011 Language Modeling Next Word Prediction Python 6.en.srt 15.2 KB
01 Introduction to Course/001 Introduction to Instructor and Aisciences.en.srt 14.6 KB
03 DNN Overview/015 Backpropagation.en.srt 14.4 KB
10 Project I_ Book Writer/006 Modling RNN Model Text Generation.en.srt 14.2 KB
04 RNN Architecture/006 ManyToMany Model.en.srt 13.4 KB
08 Vanishing Gradients in RNN/003 GRU.en.srt 13.3 KB
03 DNN Overview/002 Neuron and Perceptron.en.srt 13.2 KB
03 DNN Overview/013 DNN Training Parameters.en.srt 13.1 KB
10 Project I_ Book Writer/001 Introduction.en.srt 13.0 KB
03 DNN Overview/017 Weigth Initialization.en.srt 12.4 KB
10 Project I_ Book Writer/004 Modling RNN Model in TensorFlow.en.srt 12.3 KB
09 TensorFlow/001 Introduction to TensorFlow.en.srt 12.3 KB
12 Further Readings and Resourses/001 Further Readings and Resourses 1.en.srt 11.9 KB
11 Project II_ Stock Price Prediction/002 Data Set.en.srt 11.7 KB
08 Vanishing Gradients in RNN/008 Attention Model.en.srt 11.7 KB
04 RNN Architecture/003 Infinite Memory Architecture.en.srt 11.6 KB
03 DNN Overview/006 Number of Nuerons vs Number of Layers.en.srt 11.3 KB
01 Introduction to Course/002 Focus of the Course.en.srt 11.1 KB
03 DNN Overview/018 Batch miniBatch Stocastic.en.srt 11.1 KB
05 Gradient Decsent in RNN/008 BackPropagation Through Time.en.srt 10.5 KB
04 RNN Architecture/002 Fixed Length Memory Model.en.srt 10.5 KB
04 RNN Architecture/010 ManyToMany Different Sizes Model.en.srt 10.3 KB
07 Sentiment Classification using RNN/001 Vocabulary Implementation.en.srt 10.1 KB
06 RNN implementation/002 Automatic Diffrenciation Pytorch.en.srt 10.0 KB
03 DNN Overview/014 Gradient Descent.en.srt 9.9 KB
02 Applications of RNN (Motivation)/003 Machine Translation.en.srt 9.8 KB
03 DNN Overview/003 DNN Architecture.en.srt 9.8 KB
03 DNN Overview/012 Activation Function.en.srt 9.7 KB
04 RNN Architecture/013 Deep RNNs.en.srt 9.4 KB
05 Gradient Decsent in RNN/001 Introduction to Gradient Descent Module.en.srt 9.4 KB
08 Vanishing Gradients in RNN/002 Introduction Vanishing Gradients in RNN.en.srt 9.4 KB
02 Applications of RNN (Motivation)/001 Human Activity Recognition.en.srt 9.3 KB
08 Vanishing Gradients in RNN/005 LSTM.en.srt 9.3 KB
04 RNN Architecture/005 Notations.en.srt 9.3 KB
05 Gradient Decsent in RNN/004 Loss Function.en.srt 9.3 KB
05 Gradient Decsent in RNN/002 Example Setup.en.srt 9.2 KB
04 RNN Architecture/007 OneToMany Model.en.srt 8.9 KB
08 Vanishing Gradients in RNN/007 Bidirectional RNN.en.srt 8.7 KB
06 RNN implementation/007 Language Modeling Next Word Prediction Python 2.en.srt 8.7 KB
10 Project I_ Book Writer/005 Modling RNN Model Training.en.srt 8.7 KB
10 Project I_ Book Writer/007 Activity.en.srt 8.4 KB
08 Vanishing Gradients in RNN/001 Introduction to Better RNNs Module.en.srt 8.3 KB
05 Gradient Decsent in RNN/006 Chain Rule.en.srt 8.3 KB
03 DNN Overview/008 Universal Approximation Therorem.en.srt 8.0 KB
06 RNN implementation/008 Language Modeling Next Word Prediction Python 3.en.srt 7.7 KB
04 RNN Architecture/009 Activity Many to One.en.srt 7.7 KB
02 Applications of RNN (Motivation)/005 Stock Price Predictions.en.srt 7.6 KB
03 DNN Overview/005 Calculating Number of Weights of DNN.en.srt 7.6 KB
06 RNN implementation/006 Language Modeling Next Word Prediction Python 1.en.srt 7.6 KB
02 Applications of RNN (Motivation)/002 Image Captioning.en.srt 7.5 KB
07 Sentiment Classification using RNN/005 RNN Setup 1.en.srt 7.4 KB
11 Project II_ Stock Price Prediction/001 Problem Statement.en.srt 7.4 KB
04 RNN Architecture/001 Introduction to Module.en.srt 7.2 KB
11 Project II_ Stock Price Prediction/005 Activity.en.srt 7.1 KB
05 Gradient Decsent in RNN/005 Why Gradients.en.srt 7.1 KB
03 DNN Overview/010 Decision Boundary in DNN.en.srt 6.9 KB
08 Vanishing Gradients in RNN/009 Attention Model Optional.en.srt 6.9 KB
08 Vanishing Gradients in RNN/004 GRU Optional.en.srt 6.9 KB
02 Applications of RNN (Motivation)/004 Speech Recognition.en.srt 6.8 KB
05 Gradient Decsent in RNN/007 Chain Rule in Action.en.srt 6.8 KB
03 DNN Overview/019 Batch Normalization.en.srt 6.7 KB
07 Sentiment Classification using RNN/003 Vocabulary Implementation From File.en.srt 6.7 KB
08 Vanishing Gradients in RNN/006 LSTM Optional.en.srt 6.5 KB
03 DNN Overview/011 Bias Term.en.srt 6.5 KB
05 Gradient Decsent in RNN/003 Equations.en.srt 6.3 KB
04 RNN Architecture/008 ManyToOne Model.en.srt 6.2 KB
03 DNN Overview/007 Discriminative vs Generative Learning.en.srt 6.1 KB
03 DNN Overview/004 FeedForward FullyConnected MLP.en.srt 5.7 KB
04 RNN Architecture/011 Activity Many to Many Nmt.en.srt 5.6 KB
06 RNN implementation/009 Language Modeling Next Word Prediction Python 4.en.srt 5.5 KB
07 Sentiment Classification using RNN/004 Vectorizer.en.srt 5.4 KB
03 DNN Overview/009 Why Depth.en.srt 5.1 KB
07 Sentiment Classification using RNN/002 Vocabulary Implementation Helpers.en.srt 5.1 KB
06 RNN implementation/005 Language Modeling Next Word Prediction RNN Architecture.en.srt 4.8 KB
06 RNN implementation/001 Automatic Diffrenciation.en.srt 4.8 KB
06 RNN implementation/010 Language Modeling Next Word Prediction Python 5.en.srt 4.7 KB
03 DNN Overview/001 Introduction to Deep Learning Module.en.srt 4.4 KB
03 DNN Overview/021 Convergence Animation.en.srt 4.3 KB
03 DNN Overview/016 Training DNN Animantion.en.srt 4.3 KB
06 RNN implementation/003 Language Modeling Next Word Prediction Vocabulary Index.en.srt 4.3 KB
07 Sentiment Classification using RNN/007 WhatNext.en.srt 4.2 KB
04 RNN Architecture/012 Models Summary.en.srt 4.0 KB
06 RNN implementation/004 Language Modeling Next Word Prediction Vocabulary Index Embeddings.en.srt 3.9 KB
02 Applications of RNN (Motivation)/007 Activity.en.srt 3.0 KB
13 Bonus Lecture/001 THANK YOU Bonus Video.en.srt 2.6 KB
01 Introduction to Course/003 Request for Your Honest Review.en.srt 2.5 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 2.3 KB
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0. Websites you may like/[FreeCourseSite.com].url 127 bytes
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[FreeCourseSite.com] Udemy - Deep Learning Recurrent Neural Networks with Python

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