Exploring Data Science
Introduces readers to various areas in data science and explains which methodologies work best for each, with practical examples in R, Python, and other languages.
Tag(s): Data Science
Publication date: 01 Jun 2016
ISBN-10: n/a
ISBN-13: 9781617294181
Paperback: 186 pages
Views: 9,367
Type: Book
Publisher: Manning Publications
License: Standard Copyright License
Post time: 10 Nov 2016 09:00:00
Exploring Data Science
There's never been a better time to get into data science. But where do you start? Data Science is a broad field, incorporating aspects of statistics, machine learning, and data engineering. It's easy to become overwhelmed, or end up learning about a small section of data science or a single methodology.
Exploring Data Science is a collection of five hand-picked chapters introducing you to various areas in data science and explaining which methodologies work best for each. John Mount and Nina Zumel, authors of Practical Data Science with R, selected these chapters to give you the big picture of the many data domains. You'll learn about time series, neural networks, text analytics, and more. As you explore different modeling practices, you'll see practical examples of how R, Python, and other languages are used in data science. Along the way, you'll experience a sample of Manning books you may want to add to your library.
About The Author(s)
John Mount produces applied research, prototyping and training in information extraction, algorithms and data-mining for web-scale businesses, hedge funds and start ups, as a consultant at Win-Vector LLC. Earlier he has managed a research group at Shopping.com, performed research in biotech and been a trader in a hedge-fund.
John Mount produces applied research, prototyping and training in information extraction, algorithms and data-mining for web-scale businesses, hedge funds and start ups, as a consultant at Win-Vector LLC. Earlier he has managed a research group at Shopping.com, performed research in biotech and been a trader in a hedge-fund.
Nina Zumel is a Principal Consultant with Win-Vector LLC, a data science consulting firm based in San Francisco. Before Win-Vector, she was the co-founder and owner of an SBIR company where she conducted research and specialty software development for defense and emergency response applications. Her technical interests include data science, statistics, statistical learning, and data visualization. She is also interested (at a layperson’s level) in cognitive science, psychology, and linguistics.
Nina Zumel is a Principal Consultant with Win-Vector LLC, a data science consulting firm based in San Francisco. Before Win-Vector, she was the co-founder and owner of an SBIR company where she conducted research and specialty software development for defense and emergency response applications. Her technical interests include data science, statistics, statistical learning, and data visualization. She is also interested (at a layperson’s level) in cognitive science, psychology, and linguistics.