Looking for the best Data Science books? Browse our list to find excellent book recommendations on the subject.
- Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (2013)
- Data Science from Scratch: First Principles with Python (2019)
- Python Data Science Handbook: Essential Tools for Working with Data (2016)
- Data Science (MIT Press Essential Knowledge series) (2018)
- Storytelling with Data: A Data Visualization Guide for Business Professionals (2015)
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (2017)
- Practical Statistics for Data Scientists: 50 Essential Concepts (2017)
- Data Science for Beginners: This Book Includes – Machine Learning for Beginners + Analysis and Programming Code (2019)
- Numsense! Data Science for the Layman: No Math Added (2017)
- Heard In Data Science Interviews: Over 650 Most Commonly Asked Interview Questions & Answers (2018)
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (2013)
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the “data-analytic thinking” necessary for extracting useful knowledge and business value from the data you collect.
Data Science from Scratch: First Principles with Python (2019)
To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, and toolkits—but also understand the ideas and principles underlying them.
Python Data Science Handbook: Essential Tools for Working with Data (2016)
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data.
Data Science (MIT Press Essential Knowledge series) (2018)
The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance.
Storytelling with Data: A Data Visualization Guide for Business Professionals (2015)
Don’t simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You’ll discover the power of storytelling and the way to make data a pivotal point in your story.
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (2017)
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun.
Practical Statistics for Data Scientists: 50 Essential Concepts (2017)
Statistical methods are a key part of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective.
Data Science for Beginners: This Book Includes – Machine Learning for Beginners + Analysis and Programming Code (2019)
★★ Buy the Paperback Version of this Book on amazon.com and get the Kindle Book version for FREE ★★Have you ever wondered how speech recognition and search engines really work? Do you wish you could get a machine to do more of your tasks?
Numsense! Data Science for the Layman: No Math Added (2017)
Used as in top universities like and .Sold in and translated into .Want to get started on data science? Our promise: no math added.This book has been written in layman’s terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application.
Heard In Data Science Interviews: Over 650 Most Commonly Asked Interview Questions & Answers (2018)
A collection of over 650 actual Data Scientist/Machine Learning Engineer job interview questions along with their full answers, references, and useful tips #63,538 in Books (See Top 100 in Books) #132 in Artificial Intelligence & Semantics Would you like to ?If you are a seller for this product, would you like to ?
Best Data Science Books: The Ultimate List
We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Library Genesis and download some data science books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.
Tensors for data processing: theory, methods, and applications
Author(s): edited by Yipeng Liu.
ID: 3526711, Publisher: Elsevier Science & Technology,, Year: [2021]., Size: 18 Mb, Format: pdf
Data Science on the Google Cloud Platform, 2nd Edition
Author(s): Valliappa Lakshmanan
ID: 3125843, Publisher: O'Reilly Media, Inc., Year: 2023, Size: 4 Mb, Format: epub
Practical Data Privacy Solving Privacy and Security Problems in Your Data Science Workflow. Early Release
Author(s): Katharine Jarmul
ID: 3326983, Publisher: O'Reilly Media, Inc., Year: 2023, Size: 3 Mb, Format: epub
Please note that this booklist is not definite. Some books are absolutely record-breakers according to Washington Post, others are drafted by unknown writers. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant books you could recommend? Leave a comment if you have any feedback on the list.