Wednesday, 5 July 2017

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

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