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If you’re interested in learning more about data science, there’s no shortage of excellent resources to help you dive into this fascinating field. However, with there being so many options to choose from, such as what you can find in 23 Books for Professional Development, it can take a great deal of time and effort to determine which resources will be beneficial to you in the long run.
For that reason, we’ve created a list of the 21 best books on data science to help you get started on your learning journey. In this article, we’ll introduce you to these fantastic resources, explain what makes them the best books on data science, and give you a glimpse of what you can expect to learn from each one.
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Our List of the Best Books on Data Science
In this section, we’ll introduce you to our list of the best books on data science. We’ve carefully selected these books based on their relevance, clarity, and overall quality, ensuring that each one provides readers with a valuable learning experience.
Whether you’re looking to learn the basics of data science, improve your data analysis skills, or explore the latest data science technologies and trends, our list has something for everyone. Continue reading below to see our recommendations.
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1. “Python for Data Analysis” by Wes McKinney
This book provides full directions for navigating Python for data science.
2. “Data Science from Scratch” by Joel Grus
You can learn about data science from the very beginning.
3. “Data Science for Business” by Foster Provost and Tom Fawcett
This book outlines it all when it concerns data science and the business world.
4. “The Elements of Statistical Learning” by Trevor Hastie, Robert Tibshirani, and Jerome Friedman
You can learn about all aspects of data science with this read.
5. “Applied Predictive Modeling” by Max Kuhn and Kjell Johnson
Combining data science and modeling, this book shows various angles.
You can learn the basics of data science, improve your data analysis skills, or explore the latest data science technologies and trends.
6. “Data Smart: Using Data Science to Transform Information into Insight” by John W. Foreman
This book looks at data science from the perspective of retail opportunities.
7. “Data Science Essentials in Python” by Dmitry Zinoviev
With this book, you can learn to streamline operations in Python.
8. “Storytelling with Data” by Cole Nussbaumer Knaflic
The information in this book teaches you how to expand the data into larger environments and realities.
9. “R For Data Science” by Hadley Wickham
Hadley Wickham is a force in the data science industry and has published multiple books on the topic.
10. “Data Mining: Concepts and Techniques” by Jiawei Han, Micheline Kamber, and Jian Pei
This book gives you an extensive background on the practice of data mining and what it does for data science.
11. “The Kaggle Book: Data Analysis and Machine Learning for Competitive Data Science” by Konrad Banachewicz and Luca Massaron
With the material in this book, you can learn how to problem-solve issues you come in contact with in data science.
12. “An Introduction to Statistical Learning” by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
When you want to understand the concepts of statistics and data science, the information in this book is highly beneficial.
13. “Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More” by Matthew A. Russell
This book gives you insight as to how data science parlays into social media and the internet.
14. “Python Machine Learning” by Sebastian Raschka and Vahid Mirjalili
This guide’s information helps you incorporate Python into data science and technological implementations.
15. “Big Data: Principles and Best Practices of Scalable Real-Time Data Systems” by Nathan Marz and James Warren
Over the years, the components of data science have significantly changed and adapted to real-time circumstances, which this information highlights.
16. “The Hundred-Page Machine Learning Book” by Andriy Burkov
The primary concept of this book is to teach you what you need to know about data science in 100 pages or less.
17. “Data Science for Dummies” by Lillian Pierson
This book tells you how to use data to benefit your business and increase productivity.
18. “Fundamentals of Deep Learning” by Nikhil Buduma
Deep learning is a form of data science that many don’t think about, but the information is critical to the subject.
19. “Machine Learning for Spatial Environmental Data: Theory, Applications, and Software” by Mikhail Kanevski, Vadim Timonin, and Alexi Pozdnukhov
When you look at data science from the perspective of geography, the statistics will swing significantly due to the location. This book covers that detail.
20. “Statistical Inference via Data Science: A ModernDive into R and the Tidyverse” by Chester Ismay and Albert Y. Kim
This book is one of the most popular options when it comes to getting a comprehensive background on data science.
21. “Doing Data Science: Straight Talk from the Frontline” by Cathy O’Neil and Rachel Schutt
There are many different ways that data science can influence various aspects of life, which this book gives a thorough deep dive into.
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Final Thoughts
Learning about data science can be daunting, but with the right resources, it can be a fascinating and rewarding experience. Our list of the 21 Best Books on Data Science provides readers with diverse options, each offering valuable insights and knowledge into the field.
Whether a beginner or an experienced data scientist, these books will help you improve your skills and stay up-to-date with the latest trends and technologies. So, pick up one of these books today and start your journey to becoming a successful data scientist!
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