Books are the ocean of knowledge, and why shouldn’t they be? Books contain a plethora of wisdom shared by authors with high expertise in their respective industries. According to Statista, an American adult spends at least 20 mins a day reading. On top of this list are Indians who spend 10.42 hours reading weekly.
Are you a reading enthusiast who loves to read? Or are you someone who is looking to build this excellent habit? Suppose your answer is yes, and you want to start reading books that can also help you earn a living. In that case, this article brings you information about the best data science books that can help you learn data science skills and dominate this fast-growing industry. Our list is based on reviews on Amazon, experts’ views on Quora, and our own experience of reading these books.
So without further ado, let’s get started!
5 Best Data Science Books
Here is a list of the 5 most popular data science books that you should be reading in 2023:
1. Introducing Data Science: Big Data, Machine Learning, and More, Using Python Tools by Arno D.B. Meysman et al
This book will be your first step in understanding what data science is all about. It introduces you to the fundamentals and the basic tasks of data science. The book has 9 chapters that cover the importance of data science in big data and machine learning, the first steps in big data, the rise of graph databases, and data visualization.
With the help of this book, you will be able to learn how to use the Python language in data science. Also, you will learn how to gain insights from data sets using Python.
This book has 320 pages and is published in English by Dreamtech Press. Also, it is one of the best-selling data science books available on Amazon.
2. Practical Data Science with R (MANNING) by Nina Zumel and John Mount
Second on our list is the book that teaches us how to efficiently use the IT sector to boost your business. The book has multiple techniques that you can use in your daily business situations. It significantly focuses on three things: statistics, machine learning, and computer science, which can be used to make business models. Such business models are well known for their predictions and are used to make crucial business decisions. Apart from making predictions, the book also wants you to understand how these presentations can be presented.
Practical data science with R has 416 pages and it is published in English by Dreamteh Press. After reading this book, you will be confident about your knowledge of data science.
3. Python Data Science Handbook: Essential Tools for Working with Data by Jake VanderPlas
This data science handbook is helpful for those who want to learn how to use Python for data science. The principal characteristic of this book is that apart from Python, you will also get to learn IPython, Jupyter, Numpy, Pandas, Matplotlib, and Scikit-Learn. These are all essential skills one needs to learn to establish a strong understanding of Python. This book is exactly what you need to have in-depth practical knowledge of Python.
In its 548 pages, this book delivers five chapters that focus on Ipython, Numpy, Data manipulation, data visualization, and machine learning.
4. Data Science From Scratch: First Principles with Python, Second Edition by Joel Grus
Another book that is suitable for beginners is Data Science from Scratch. The reason we included this book on our list is that it not only makes you familiar with various Data Science tools, including frameworks, libraries, and modules, but also helps you learn the ideas and principles underlying them.
This book demonstrates how various Data Science tools work and what algorithms they use. Also, if you are good at Mathematics, this book will help you gain an in-depth understanding of statistics, which is at the core of data science. You will get to learn about linear algebra and probability, and how they are used in data science.
5. Practical Statistics for Data Scientists, 2e: 50+ Essential Concepts Using R and Python by Andrew Bruce et al
Last but not least, the Practical Statistics for Data Scientists is a 350-page data science book. This book is a little more expensive than the others listed above, but it is a value for money since it covers a wide range of data science concepts. The book talks about all the essential data science topics and summarizes them really well.
The best thing about this data science book is that it is beginner-friendly. It has seven chapters that covers various topics, including Exploratory Data Analysis, Data and Sampling Distribution, Statistical Experiments and Significance Testing, Regression and Prediction, Classification, Statistical Machine Learning, and Unsupervised Learning.
Conclusion
Reading books is a great way to start learning something. It is advantageous to read these books if you want to pursue a career in the field of data science. The books that we have listed above are excellent for beginners. They will undoubtedly help you to gain the knowledge required to become a data science professional. There are plenty of data science books to learn data science, but to start with zero, we recommend you go through the aforementioned books at least once during your career.
All the best for your future!
