Machine Learning with Python Cookbook PDF

Download Machine Learning with Python Cookbook PDF by Chris Albon published in 2018. This a complete guide to solving the machine learning challenges you might be facing every day.

Reviews of Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

Inside this book: Over the last few years, machine learning has become embedded in a wide variety of day-to-day business, nonprofit, and government operations. As the popularity of machine learning increased, a cottage industry of high-quality literature that taught applied machine learning to practitioners developed. This literature has been highly successful in training an entire generation of data scientists and machine learning engineers. This literature also approached the topic of machine learning from the perspective of providing a learning resource to teach an individual what machine learning is and how it works. However, while fruitful, this approach left out a different perspective on the topic: the nuts and bolts of doing machine learning day to day. That is the motivation of this book—not as a tome of machine learning knowledge for the student but as a wrench for the professional, to sit with dog-eared pages on desks ready to solve the practical day-to-day problems of a machine learning practitioner.

Who This Book Is For?

This book is not an introduction to machine learning. If you are not comfortable with the basic concepts of machine learning or have never spent time learning machine learning, do not buy this book. Instead, this book is for the machine learning practitioner who, while comfortable with the theory and concepts of machine learning, would benefit from a quick reference containing code to solve challenges he runs into working on machine learning on an everyday basis. This book assumes the reader is comfortable with the Python programming language and package management.

Terminology Used in This Book

Machine learning draws upon techniques from a wide range of fields, including computer science, statistics, and mathematics. For this reason, there is significant variation in the terminology used in the discussions of machine learning:

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