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A series of Deep Learning breakthroughs have boosted the whole field of machine learning over the last decade. Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.
This hands-on book shows you how to use:
Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry point
TensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networks
Practical code examples that you can apply without learning excessive machine learning theory or algorithm details
Chapter 1The Machine Learning landscape
Chapter 2End-to-end Machine Learning project
Chapter 4Training Linear Models
Chapter 5Support Vector Machines
Chapter 6Decision Trees and Random Forests
Chapter 7Ensemble Methods
Chapter 8Dimensionality Reduction
Chapter 9Up and Running with TensorFlow
Chapter 10Introduction to Artificial Neural Networks
Chapter 11Training Deep Neural Nets
Chapter 12Distributing TensorFlow across Devices and Servers
Chapter 13Convolutional Neural Networks
Chapter 14Recurrent Neural Networks
Chapter 16Reinforcement Learning
Appendix AExercise Solutions
Appendix BMachine Learning Project Checklist
Appendix CSVM Dual Problem
Appendix EOther popular ANN architectures
Hands-On Machine Learning with Scikit-Learn and TensorFlow
Aurelien Geron has worked as a software engineer for a consulting firm in Paris, an IoT startup in Montreal (back in 1999!), and has also worked as co-founder and CTO of a leading wireless ISP in France (Wifirst). He was the product manager for YouTube's video classification team.
He has authored a WiFi book, a C++ book, and taught CS in French engineering schools. A few personal fun facts: Aurelien grew up in France, Nigeria, New Zealand, and the U.S. (Berkeley). He studied microbiology and evolutionary genetics before going into software engineering. He was the singer in a rock band, has 2 turtles and 3 hens, has scuba dived with 10-foot sharks, taught his 5-year-old son to count in binary on his fingers (up to 1023), and his parachute didn't open on the 2nd jump.
Comments about oreilly Hands-On Machine Learning with Scikit-Learn and TensorFlow:
Hands On Machine Learning, that's exactly what it is. From chapter 2 on, you are given full power: it's not just theory, it is full-blown practice. The author is very comprehensive, must have been a teacher of some sort. Excellent in every possible way.
Bottom Line Yes, I would recommend this to a friend