This is the official code repository for Machine Learning with TensorFlow.
Get started with machine learning using TensorFlow, Google's latest and greatest machine learning library.
Summary
Chapter 2 - TensorFlow Basics
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Concept 1: Defining tensors
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Concept 2: Evaluating ops
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Concept 3: Interactive session
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Concept 4: Session loggings
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Concept 5: Variables
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Concept 6: Saving variables
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Concept 7: Loading variables
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Concept 8: TensorBoard
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Concept 1: Linear regression
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Concept 2: Polynomial regression
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Concept 3: Regularization
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Concept 1: Linear regression for classification
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Concept 2: Logistic regression
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Concept 3: 2D Logistic regression
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Concept 4: Softmax classification
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Concept 1: Clustering
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Concept 2: Segmentation
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Concept 3: Self-organizing map
Chapter 6 - Hidden markov models
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Concept 1: Forward algorithm
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Concept 2: Viterbi decode
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Concept 1: Autoencoder
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Concept 2: Applying an autoencoder to images
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Concept 3: Denoising autoencoder
Chapter 8 - Reinforcement learning
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Concept 1: Reinforcement learning
Chapter 9 - Convolutional Neural Networks
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Concept 1: Using CIFAR-10 dataset
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Concept 2: Convolutions
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Concept 3: Convolutional neural network
Chapter 10 - Recurrent Neural Network
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Concept 1: Loading timeseries data
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Concept 2: Recurrent neural networks
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Concept 3: Applying RNN to real-world data for timeseries prediction
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Concept 1: Multi-cell RNN
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Concept 2: Embedding lookup
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Concept 3: Seq2seq model
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Concept 1: RankNet
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Concept 2: Image embedding
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Concept 3: Image ranking