Exploration machine learning, the use of Scikit-Learn tracking a machine-learning project examples; explore various training model; use TensorFlow library to build and train the neural network, in-depth neural network architecture, including convolution neural networks, recurrent neural network and the depth of reinforcement learning , learning and scaling can be used to train the neural network technology depth.
It divided into two parts. The first part is Chapter 1 to Chapter 8, basic theory and basic knowledge of machine learning algorithms covering - from linear regression to random forests, to help the reader master the common method Scikit-Learn; the second part to the first Chapter 9 Chapter 16 discusses the depth of learning and common framework TensorFlow, takes the reader step by step to set up and use TensorFlow depth training the neural network, and convolution neural network.
Suggested reading:
"Machine learning based on real Scikit-Learn and TensorFlow" Chinese high-definition version of PDF, 649 pages, with a table of contents, text can be copied; HD English PDF, 564 pages, with a table of contents, text can be copied; the English version of the two can be compared to learning. Supporting source code;
Network disk download: http://106.13.73.98
