Chapman & Hall/CRC Data Science Series
About the Book 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.
Data Science: A First Introduction with Python
1st Edition
By Tiffany Timbers, Trevor Campbell, Melissa Lee, Joel Ostblom, Lindsey Heagy
August 23, 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
2nd Edition
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 ...
DevOps for Data Science
1st Edition
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
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
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
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
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
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
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...
Data Science in Practice
1st Edition
By Tom Alby
September 22, 2023
Data Science in Practice is the ideal introduction to data science. With or without math skills, here, you get the all-round view that you need for your projects. This book describes how to properly question data, in order to unearth the treasure that data can be. You will get to know the relevant ...
Big Data Analytics: A Guide to Data Science Practitioners Making the Transition to Big Data
1st Edition
By Ulrich Matter
September 04, 2023
Successfully navigating the data-driven economy presupposes a certain understanding of the technologies and methods to gain insights from Big Data. This book aims to help data science practitioners to successfully manage the transition to Big Data. Building on familiar content from applied ...
Telling Stories with Data: With Applications in R
1st Edition
By Rohan Alexander
July 27, 2023
The book equips students with the end-to-end skills needed to do data science. That means gathering, cleaning, preparing, and sharing data, then using statistical models to analyse data, writing about the results of those models, drawing conclusions from them, and finally, using the cloud to put a ...