Introduction to Statistical and Machine Learning Methods for Data Science

By: Carlos Andre Reis Pinheiro, Mike Patetta

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Hardcover | 28 July 2021

At a Glance

Hardcover
170 Pages

Dimensions(cm)
23.5 x 19.05 x 1.12

Hardcover

$81.75

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Boost your understanding of data science techniques to solve real-world problems

Data science is an exciting, interdisciplinary field that extracts insights from data to solve business problems. This book introduces common data science techniques and methods and shows you how to apply them in real-world case studies. From data preparation and exploration to model assessment and deployment, this book describes every stage of the analytics life cycle, including a comprehensive overview of unsupervised and supervised machine learning techniques. The book guides you through the necessary steps to pick the best techniques and models and then implement those models to successfully address the original business need.

No software is shown in the book, and mathematical details are kept to a minimum. This allows you to develop an understanding of the fundamentals of data science, no matter what background or experience level you have.

Industry Reviews

"We've all heard the term "Data Science," but what does it mean? Obviously, it involves both data and science, but doesn't everything? Yes! But it's not as easy as it sounds. Luckily, the authors of this book have swept in to rescue us from this modern-day thought paradox by gently walking us through the maze of research, development, theory, and application that is the world of machine learning and data science. Geared to anyone interested in learning more about this intricate study, this book will help answer your most pressing questions, while opening up the doors of possibility to many more. A must-have for the desk of anyone even remotely involved in research!"

Deanna (DeDe) Naomi Schreiber-Gregory, MS

Co-owner, Operations and Finance

Independent Consultant - Statistics & Data Management

Juxdapoze, LLC

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