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Think Like a Data Scientist: Tackle the data science process stepbystep,Used
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SummaryThink Like a Data Scientist presents a stepbystep approach to data science, combining analytic, programming, and business perspectives into easytodigest techniques and thought processes for solving real world datacentric problems.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyData 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.About the BookThink Like a Data Scientist teaches you a stepbystep approach to solving realworld datacentric 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 InsideThe data science process, stepbystep How to anticipate problems Dealing with uncertainty Best practices in software and scientific thinkingAbout the ReaderReaders need beginner programming skills and knowledge of basic statistics.About the AuthorBrian Godsey has worked in software, academia, finance, and defense and has launched several datacentric startups.Table of ContentsPART 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
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