Mastering TensorFlow -2018 pdf

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What this book covers Chapter 1 , TensorFlow 101, recaps the basics of TensorFlow, such as how to create tensors, constants, variables, placeholders, and operations. We learn about computation graphs and how to place computation graph nodes on various devices such as GPU. We also learn how to use TensorBoard to visualize various intermediate and final output values. Chapter 2 , High-Level Libraries for TensorFLow, covers several high- level libraries such as TF Contrib Learn, TF Slim, TFLearn, Sonnet, and Pretty Tensor. Chapter 3 , Keras 101, gives a detailed overview of the high-level library Keras, which is now part of the TensorFlow core. Chapter 4 , Classical Machine Learning with TensorFlow, teaches us to use TensorFlow to implement classical machine learning algorithms, such as linear regression and classification with logistic regression. Chapter 5 , Neural Networks and MLP with TensorFlow and Keras, introduces the concept of neural networks and shows how to build simple neural network models. We also cover how to build deep neural network models known as MultiLayer Perceptrons. Chapter 6 , RNNs with TensorFlow and Keras, covers how to build Recurrent Neural Networks with TensorFlow and Keras. We cover the internal architecture of RNN, Long Short-Term Networks (LSTM), and Gated Recurrent Units (GRU). We provide a brief overview of the API functions and classes provided by TensorFlow and Keras to implement RNN models. Chapter 7 , RNN for Time Series Data with TensorFlow and Keras, shows how to build and train RNN models for time series data and provide examples in TensorFlow and Keras libraries. Chapter 8 , RNN for Text Data with TensorFlow and Keras, teaches us how to build and train RNN models for text data and provides examples in TensorFlow and Keras libraries. We learn to build word vectors and embeddings with TensorFlow and Keras, followed by LSTM models for using embeddings to generate text from sample text data. Chapter 9 , CNN with TensorFlow and Ker

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风中之尘09 版本有些乱,但内容还是不错的。
iorichang 不建议下载,应该是别的格式转过来的,里面的公式太乱了。。。
wyf200913866 不错 挺好的 使用
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