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A Hands-On Introduction to Data Science with Python
A Hands-On Introduction to Data Science with Python
Knygos.lt klubas Knygos.lt nariams
95,61 €
-30%
Įprastai
136,59 €
  • Išsiųsime per 12–18 d.d.
Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool Python, a new chapter on using Python for statistical analysis, and a new chapter that demonstrates how to use Python within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in…

A Hands-On Introduction to Data Science with Python (el. knyga) (skaityta knyga) | knygos.lt

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Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool Python, a new chapter on using Python for statistical analysis, and a new chapter that demonstrates how to use Python within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in a new end-to-end project in Chapter 11. New 'Data Science in Practice' boxes highlight how concepts introduced work within an industry context and many chapters include new sections on AI and Generative AI. A suite of online material for instructors provides a strong supplement to the book, including lecture slides, solutions, additional assessment material and curriculum suggestions. Datasets and code are available for students online. This entry-level textbook is ideal for readers from a range of disciplines wishing to build a practical, working knowledge of data science.

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Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool Python, a new chapter on using Python for statistical analysis, and a new chapter that demonstrates how to use Python within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in a new end-to-end project in Chapter 11. New 'Data Science in Practice' boxes highlight how concepts introduced work within an industry context and many chapters include new sections on AI and Generative AI. A suite of online material for instructors provides a strong supplement to the book, including lecture slides, solutions, additional assessment material and curriculum suggestions. Datasets and code are available for students online. This entry-level textbook is ideal for readers from a range of disciplines wishing to build a practical, working knowledge of data science.

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