Think like a data scientist: tackle the data science process step-by-step, brian godsey
Описание
Summary
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 Technology
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.
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.
About the Author
Brian Godsey
has worked in software, academia, finance, and defense and has launched
several data-centric start-ups.
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
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