This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to provide Machine Learning support to their existing projects, and see them get implemented effectively .Computer science researchers, data scientists, Artificial Intelligence programmers, and statistical programmers would equally gain from this book and would learn about effective implementation through lots of the practical examples discussed.Readers need no prior experience with Machine Learning or statistical processing. Python development experience is assumed.

About the Author
Willi Richert has a PhD in Machine Learning/Robotics and currently works for Microsoft in the Bing Core Relevance Team. He performs statistical machine translation. Luis Pedro Coelho has over 10 years of experience in Machine Learning. He has a PhD from the School of Computer Science at Carnegie Mellon University, which is a very strong school in Machine Learning, and currently works in Computational Biology.


Book Information
ISBN 9781782161400
Author Willi Richert
Page Count 290
Imprint Packt Publishing Limited
Publisher Packt Publishing Limited