Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance by Puneet Mathur


Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance
Title : Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance
Author :
Rating :
ISBN : 1484237862
ISBN-10 : 9781484237861
Format Type : Paperback
Number of Pages : 379
Publication : Published December 13, 2018

Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you'll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented.
Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You'll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning.

What You Will Learn
Discover applied machine learning processes and principles


Implement machine learning in areas of healthcare, finance, and retail


Avoid the pitfalls of implementing applied machine learning


Build Python machine learning examples in the three subject areas



Who This Book Is For
Data scientists and machine learning professionals.


Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance Reviews


  • Islomjon

    Actually, I was not expecting panacea for ML pipelines by reading this book. However, being massive 384 pages are spent for problem definitions that are loosely related to ML industry. The book as if written from conference speeches frim different topics, author has a very little knowledge how to write technical books with precise concepts. It has a lot of typos, meanigless explanations and, how author claims, ideas for monetizing ML, but without ML entirely.

    In contrast, Puneed Mathur did a good job in analyzing datasets giving the key insights where to pay attention and draw conclusions. Anyway, even the statistical analysis was in the degree of school student who tries to explain unnecessary and obvious things just to fill pages with words.