Table of Contents

1. Introduction
2. Machine Learning for Hackers: Case Studies and Algorithms to Get You Started
3. Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists
4. Interactive Data Visualization for the Web: An Introduction to Designing with D3
5. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
6. Machine Learning in Action
7. R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (O’reilly Cookbooks)
8. Doing Data Science: Straight Talk from the Frontline
9. The Art of R Programming: A Tour of Statistical Software Design 1st Edition
10. Learning R: A Step-by-Step Function Guide to Data Analysis
11. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
12. Summary
13. References

Introduction

I am not affiliated with any of these books or authors.

I will be discussing the top 10 Data Science books [2]. The group of books are either in Kindle format or paperback, generally, the cheaper option is Kindle. You can also buy new or used for paperback in order to save some money. For Kindle, you can have the option to rent for the cheaper alternative.

The topics covered over these 10 books range from Data Science for business, R programming, Python programming, visualization, data analysis, and Machine Learning. Because these books are ranked hourly, they may change by the time you are reading this article. Similarly, the price of these books may change over time.

Below, I will highlight the top 10 books for Data Science, along with their respective costs, and will share some information on and opinions on the main topics covered in each book.

#education #data-science #technology #machine-learning #learning