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Chapman & Hall/CRC Data Science Series


About the Series

Reflecting the interdisciplinary nature of the field, this new book series brings together researchers, practitioners, and instructors from statistics, computer science, machine learning, and analytics. The series will publish cutting-edge research, industry applications, and textbooks in data science.

Features:

  • Presents the latest research and applications in the field, including new statistical and computational techniques
  • Covers a broad range of interdisciplinary topics
  • Provides guidance on the use of software for data science, including R, Python, and Julia
  • Includes both introductory and advanced material for students and professionals
  • Presents concepts while assuming minimal theoretical background

The scope of the series is broad, including titles in machine learning, pattern recognition, predictive analytics, business analytics, visualization, programming, software, learning analytics, data collection and wrangling, interactive graphics, reproducible research, and more. The inclusion of examples, applications, and code implementation is essential.

Please Contact Us if you have an idea for a book for the series.

42 Series Titles

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Mathematical Engineering of Deep Learning

Mathematical Engineering of Deep Learning

1st Edition

Forthcoming

By Benoit Liquet, Sarat Moka, Yoni (Jonathan) Nazarathy
October 03, 2024

Mathematical Engineering of Deep Learning provides a complete and concise overview of deep learning using the language of mathematics. The book  provides a self-contained background on machine learning and optimization algorithms, and progresses through the key ideas of deep learning. These ideas ...

Why Data Science Projects Fail The Harsh Realities of Implementing AI and Analytics, without the Hype

Why Data Science Projects Fail: The Harsh Realities of Implementing AI and Analytics, without the Hype

1st Edition

Forthcoming

By Douglas Gray, Evan Shellsear
September 10, 2024

The field of artificial intelligence, data science and analytics is crippling itself. Exaggerated promises of unrealistic technologies, simplifications of complex projects and marketing hype are leading to an erosion of trust in one of our most critical approaches to making decisions: data driven. ...

Data Science A First Introduction with Python

Data Science: A First Introduction with Python

1st Edition

Forthcoming

By Tiffany Timbers, Trevor Campbell, Melissa Lee, Joel Ostblom, Lindsey Heagy
August 26, 2024

Data Science: A First Introduction with Python focuses on using the Python programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. It emphasizes ...

Introduction to Data Science Data Wrangling and Visualization with R

Introduction to Data Science: Data Wrangling and Visualization with R

2nd Edition

Forthcoming

By Rafael A. Irizarry
August 02, 2024

Unlike the first edition, the new edition has been split into two books. Thoroughly revised and updated, this is the first book of the second edition of Introduction to Data Science: Data Wrangling and Visualization with R. It introduces skills that can help you tackle real-world data analysis ...

Getting (more out of) Graphics Practice and Principles of Data Visualisation

Getting (more out of) Graphics: Practice and Principles of Data Visualisation

1st Edition

Forthcoming

By Antony Unwin
July 12, 2024

Data graphics are used extensively to present information. Understanding graphics is a lot about understanding the data represented by the graphics, having a feel not just for the numbers themselves, the reliability and uncertainty associated with them, but also for what they mean. This book ...

DevOps for Data Science

DevOps for Data Science

1st Edition

Forthcoming

By Alex Gold
June 19, 2024

Data Scientists are experts at analyzing, modelling and visualizing data but, at one point or another, have all encountered difficulties in collaborating with or delivering their work to the people and systems that matter. Born out of the agile software movement, DevOps is a set of practices, ...

The Data Preparation Journey Finding Your Way with R

The Data Preparation Journey: Finding Your Way with R

1st Edition

By Martin Hugh Monkman
May 07, 2024

The Data Preparation Journey: Finding Your Way With R introduces the principles of data preparation within in a systematic approach that follows a typical data science or statistical workflow. With that context, readers will work through practical solutions to resolving problems in data using the ...

Research Software Engineering A Guide to the Open Source Ecosystem

Research Software Engineering: A Guide to the Open Source Ecosystem

1st Edition

By Matthias Bannert
April 17, 2024

Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for ...

Soccer Analytics An Introduction Using R

Soccer Analytics: An Introduction Using R

1st Edition

By Clive Beggs
March 11, 2024

Sports analytics is on the rise, with top soccer clubs, bookmakers, and broadcasters all employing statisticians and data scientists to gain an edge over their competitors. Many popular books have been written exploring the mathematics of soccer. However, few supply details on how soccer data can ...

Introduction to NFL Analytics with R

Introduction to NFL Analytics with R

1st Edition

By Bradley J. Congelio
December 19, 2023

It has become difficult to ignore the analytics movement within the NFL. An increasing number of coaches openly integrate advanced numbers into their game plans, and commentators, throughout broadcasts, regularly use terms such as air yards, CPOE, and EPA on a casual basis. This rapid growth, ...

Spatial Statistics for Data Science Theory and Practice with R

Spatial Statistics for Data Science: Theory and Practice with R

1st Edition

By Paula Moraga
December 08, 2023

Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and visualization techniques...

Data Science for Sensory and Consumer Scientists

Data Science for Sensory and Consumer Scientists

1st Edition

By Thierry Worch, Julien Delarue, Vanessa Rios De Souza, John Ennis
September 29, 2023

Data Science for Sensory and Consumer Scientists is a comprehensive textbook that provides a practical guide to using data science in the field of sensory and consumer science through real-world applications. It covers key topics including data manipulation, preparation, visualization, and analysis...

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