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Think Like a Data Scientist: Tackle the data science process step-by-step
Author : Brian Godsey
Publisher : Manning; 1st edition (April 2, 2017)
Language : English
Paperback : 328 Pages
1) Book Description
Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems.
About the Book
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
About the Reader
Readers need beginner programming skills and knowledge of basic statistics.
Table of Contents
PART 1 - PREPARING AND GATHERING DATA AND KNOWLEDGE
Philosophies of data science
Setting goals by asking good questions
Data all around us: the virtual wilderness
Data wrangling: from capture to domestication
Data assessment: poking and prodding
PART 2 - BUILDING A PRODUCT WITH SOFTWARE AND STATISTICS
Developing a plan
Statistics and modeling: concepts and foundations
Software: statistics in action
Supplementary software: bigger, faster, more efficient
Plan execution: putting it all together
PART 3 - FINISHING OFF THE PRODUCT AND WRAPPING UP
Delivering a product
After product delivery: problems and revisions
Wrapping up: putting the project away
2) About Author
Brian Godsey has worked in software, academia, finance, and defense and has launched several data-centric start-ups.

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