Books Recommendation: Hands-On Machine Learning with Scikit-Learn and TensorFlow

This hands-on book (Link:Hands-On MachineLearning with Scikit-Learn and TensorFlow) shows you how to:

• Explore the machine learning landscape, particularly neural nets.
• Use scikit-learn to track an example machine-learning project end-to-end.
• Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods.
• Use the TensorFlow library to build and train neural nets.
• Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning. 
• Learn techniques for training and scaling deep neural nets.
• Apply practical code examples without acquiring excessive machine learning theory or algorithm details

MAIN CONTENTS 

¨      The Machine Learning Landscape

§  What Is Machine Learning?

§  Why Use Machine Learning?

§  Types of Machine Learning Systems

§  Main Challenges of Machine Learning

¨      End-to-End Machine Learning Project

§  Prepare the Data for Machine Learning Algorithms

¨      Neural Networks and Deep Learning

¨      Up and Running with TensorFlow

¨      Introduction to Artificial Neural Networks

¨      Training Deep Neural Nets

¨      Distributing TensorFlow Across Devices and Servers

¨      Convolutional Neural Networks

¨      Recurrent Neural Networks

¨      Autoencoders

Link:Hands-On MachineLearning with Scikit-Learn and TensorFlow