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A Hands-On Introduction to Data Science by Chirag Shah - Book Review


Summary

Realistically and openly, this book explores the field of data science, using a hands-on approach that does not presume any previous knowledge of the topic. The fundamental data science ideas and techniques are presented independently of technology, enabling students to quickly establish a firm understanding of the subject without a full technological context and present material that will continue to be necessary even after instruments And changing technologies.

The book provides many real-life applications using popular data science tools like Python and R, with experience varying from small to big data. A suite of online resources offers a valuable complement to the book for both teachers and students, including datasets, chapter slides, solutions, sample tests, and recommendations for the curriculum. This entry-level textbook is best suited to readers from various disciplines who wish to acquire realistic, working data science knowledge.

Commentary

He is an assistant professor at the Information School in the Washington Department of (iSchool). He is the InfoSeeking Lab's Chief Executive, which focuses on information goals, human-computer interaction (HCI), and social media. He is supported by grants from the National Science Foundation, Amazon, Google, Yahoo, the National Institute for Health (NIH), and the Museum and Library Services Organization (IMLS). Shah's study includes collaborative knowledge retrieval/search and recommendation systems studies, discussing different issues with lab and field user studies, and creating computer models with machine learning techniques.

He has worked as a consultant on numerous data analysis initiatives concerning social and political issues, peacekeeping, climate change, and energy for the United Nations Data Analytics. He holds an Amazon Scholar position and works with Amazon on cutting-edge research topics around personalization and suggestion. Shah earned a Ph.D. from the University of North Carolina (UNC) at Chapel Hill in Information Technology. He runs the InfoSeeking Lab (http://infoseeking.org/) at Rutgers, where he discusses topics related to the search for information, digital processing of information, and social media.

Supported by the National Science Foundation (NSF), the Museum and Library Services Institute (IMLS), Google, and Yahoo! More about him can be found from his homepage: http://chiragshah.org/ Social Media Data Analytics was developed when he was a faculty member at Rutgers University's School of Communication and Intelligence.

As the newest winner of the Karen Spärck Jones Prize, Shah, a career achievement award in the area of processing and communication collection of natural language, an associate professor at the University of Washington Information School, was recently honored.

In honor of an influential computer scientist and pioneer in the field who died in 2007, Shah is the 11th recipient of the prize, granted by the British Computer Society Information Retrieval Specialist Community. The award, funded by Microsoft Research, goes to a thought leader in the field who has made his mark in either academia or industry.

Chirag Shah, an associate professor at the Washington Information School University, was recently honored as the current recipient of the Karen Spärck Jones Prize, a career achievement award in the processing and retrieving of information in the field of natural language.

In honor of an influential computer scientist and pioneer in the field who died in 2007, Shah is the 11th recipient of the prize, granted by the British Computer Society Information Retrieval Specialist Community. The award, funded by Microsoft Research, goes to a thought leader in the field who has made his mark in either academia or industry.

He is a well-recognized thought leader in the areas of collaborative and social information seeking. Chirag is a very well thought leader in the areas of collaborative and social information searching. A leader in the analysis and collection of competitive data from social information, having identified and formed these disciplines and establishing himself as a foremost expert in these fields.

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