binroot

TensorFlow-Book

# [Machine Learning with TensorFlow](http://www.tensorflowbook.com/) [This](https://github.com/BinRoot/TensorFlow-Book) is the official code repository for [Machine Learning with TensorFlow](http://www.tensorflowbook.com/). Get started with machine learning using TensorFlow, Google's latest and greatest machine learning library. # Summary ## [Chapter 2](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch02_basics) - TensorFlow Basics - **Concept 1**: Defining tensors - **Concept 2**: Evaluating ops - **Concept 3**: Interactive session - **Concept 4**: Session loggings - **Concept 5**: Variables - **Concept 6**: Saving variables - **Concept 7**: Loading variables - **Concept 8**: TensorBoard ## [Chapter 3](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch03_regression) - Regression - **Concept 1**: Linear regression - **Concept 2**: Polynomial regression - **Concept 3**: Regularization ## [Chapter 4](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch04_classification) - Classification - **Concept 1**: Linear regression for classification - **Concept 2**: Logistic regression - **Concept 3**: 2D Logistic regression - **Concept 4**: Softmax classification ## [Chapter 5](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch05_clustering) - Clustering - **Concept 1**: Clustering - **Concept 2**: Segmentation - **Concept 3**: Self-organizing map ## [Chapter 6](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch06_hmm) - Hidden markov models - **Concept 1**: Forward algorithm - **Concept 2**: Viterbi decode ## [Chapter 7](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch07_autoencoder) - Autoencoders - **Concept 1**: Autoencoder - **Concept 2**: Applying an autoencoder to images - **Concept 3**: Denoising autoencoder ## [Chapter 8](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch08_rl) - Reinforcement learning - **Concept 1**: Reinforcement learning ## [Chapter 9](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch09_cnn) - Convolutional Neural Networks - **Concept 1**: Using CIFAR-10 dataset - **Concept 2**: Convolutions - **Concept 3**: Convolutional neural network ## [Chapter 10](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch10_rnn) - Recurrent Neural Network - **Concept 1**: Loading timeseries data - **Concept 2**: Recurrent neural networks - **Concept 3**: Applying RNN to real-world data for timeseries prediction ## [Chapter 11](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch11_seq2seq) - Seq2Seq Model - **Concept 1**: Multi-cell RNN - **Concept 2**: Embedding lookup - **Concept 3**: Seq2seq model ## [Chapter 12](https://github.com/BinRoot/TensorFlow-Book/tree/master/ch12_rank) - Ranking - **Concept 1**: RankNet - **Concept 2**: Image embedding - **Concept 3**: Image ranking