best books for datascience

What are the best books for Data Science to read in 2023?

Starting a career in data science requires a lot of theoretical understanding for beginners to obtain the best roles in this field. Here is the answer to your question know what are the books for data science to read in 2022. They provide an in-depth understanding of data science concepts along with roles in data analysis and machine learning. The book must be covering the criteria like depth to learn everything from scratch, comprehensiveness to understand the complex concepts easily, readability to learn quickly, and applicability to implement the concepts in real-world applications. Following are the top 5 books to understand the data science concepts clearly and efficiently.

Machine Learning Simplified

Machine Learning Simplified is the new book published to cover the fundamentals of machine learning and it will impress with its uniqueness compared to others. If you are fresher or new to data science concepts, it will be suitable for you for the following reasons.

This book is written by Andrew Wolf and it comprehensively covers the core concepts required for understanding data preparation, data modeling, and mathematics along with explaining to answer what and how. It clearly explains complex data science concepts and algorithms with real-life examples that make a complete understanding of conceptual things practically. Machine Learning Simplified is the book that is supplemented with a GitHub repository and it contains actual python codes to implement for practicing along with every topic.

Practical Statistics for Data Scientists

This book is written by Peter Bruce and Andrew Bruce and it is similar to the previous book as it has both detailed and comprehensive. The only difference is that the practical statistics for data scientists book focuses on statistics more than machine learning. It covers all the core concepts we want to know in statistics, sampling distributions, descriptive statistics, A/B testing, hypothesis testing, and prediction. Practical statistics for data scientist books include code snippets in Python and R and it allows readers to practice the theoretical concepts efficiently.

Python Data Science Handbook

If you feel confident and comfortable in your coding skill, you can choose Python Data Science Handbook to understand the concepts of data science thoroughly. It helps you explore Python libraries and it is an in-depth guide for understanding Python Libraries like Pandas, Matplotlib, NumPy, Scikit-learn, and so on. This book allows you to convert your data skills into analysis better for producing data visualizations to expose your findings. Jake VanderPlas is the author of the Python Data Science Handbook and it will help you know a lot about the current day-to-day progress of data scientists.

Python for Data Analysis

Python for Data Analysis is the book that provides complete guidance on manipulating, cleansing, processing, and crunching datasets in Python. You will understand the recent versions of Pandas, IPython, NumPy, etc to equip you with practical case studies. It is highly recommended for data scientists to learn how to solve real-world data analysis problems wisely. Data wrangling is the most used process of data scientists and reading Python for Data Analysis book makes you reduce the amount of time spent on it along with the libraries and tools mentioned in this book.

Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Studies

This book is written by Matt Taddy to explain basic data science concepts from a business perspective and makes everything implementable for a business setting. Business Data Science is the only book that addresses many primary things required for business processing with data science along with a clear explanation of how data science brings value to a business. You will learn the fundamentals of machine learning through this book and it makes you proficient with an idea that explains how to implement theoretical concepts in a business setting. It also covers how to write R code to apply the written solutions to practical business problems.


Hope the suggestions of data science books help you understand the complete and complex concepts of data science, machine learning, R, Python, and data visualization along with practical exercises. Learn how to start your data science journey in our Data Science Course in Chennai at Softlogic.

Leave a Comment