Think Like a Data Scientist: Tackle the Data Science Process Step-by-Step Brian Godsey
Data collected from customers, scientific measurements, IoT sensors, and so on is valuable only if you understand it. Data scientists revel in the interesting and rewarding challenge of observing, exploring, analyzing, and interpreting this data. Getting started with data science means more than mastering analytic tools and techniques, however; the real magic happens when you begin to think like a data scientist. This book will get you there.Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you’ll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data. As you read, you’ll discover (or remember) valuable statistical techniques and explore powerful data science software. More importantly, you’ll put this knowledge together using a structured process for data science. When you’ve finished, you’ll have a strong foundation for a lifetime of data science learning and practice.What’s Inside
• The data science process, step-by-step
• How to anticipate problems
• Dealing with uncertainty
• Best practices in software and scientific thinking
Readers need beginner programming skills and knowledge of basic statistics. Brian Godsey has worked in software, academia, finance, and defense and has launched several data-centric start-ups. Categories:
Computers – Databases
Year:
2017
Edition:
1
Publisher:
Manning Publications
Language:
english
Pages:
306 / 331
ISBN 10:
1633430278
ISBN 13:
9781633430273
File:
21 MB
Think Like a Data Scientist: Tackle the Data Science Process Step-by-Step
$15.99
Think Like a Data Scientist: Tackle the Data Science Process Step-by-Step
Authors: Brian Godsey
Year: 2017
Publisher: Manning Publications
Language: English
ISBN 13: 9781633430273
ISBN 10: 1633430278
Categories: Computers, Databases
Pages: 320 / 319
Edition: 1
Availability: 5000 in stock
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