Are you looking for the **Best Books on Data Science?** but you confused about which book to choose. So, don’t worry. Your search will end after reading this article. In this article, I will discuss the Top 15 **Best Books on Data Science**. So read this full article, and choose the best book for you.

Let’s get started-

## **Best Books on Data Science**

Data Science is one of the most popular fields. Data Science offers a high salary. Everyone is trying to come to the Data Science field.

In order to learn Data Science, there are various resources available. Such as Courses, Books, Videos, and many more. But if you want to get in-depth knowledge in Data Science, then reading books is the best method to understand the concepts of Data Science.

Books give you in-depth knowledge starting from basics to advanced level. But there are lots of books available in the market. Most of the time, we get confused while choosing the best book. That’s why I have selected the best books for you based on my experience. You don’t need to struggle for searching for the best book.

Before, moving to the books, I would like to mention the skills required for Data Scientist. So, the most demanding skills for the Data Science field are-

- Programming Skills
- Statistics or Probability
- Machine Learning
- Multivariate Calculus and Linear Algebra
- Data wrangling.
- Data Visualization.
- Database Management
- BigData

For more details regarding skills, read this article- Data Science: Top 8 Most Demanding Skills to Get You Hired. So, now we talked about Data Science Skills, let’s move into **Best Books on Data Science**.

To become a Data Scientist, you should have knowledge of **Programming, Machine Learning, Probability, Statistics, and Linear Algebra.**

That’s why I have divided this article into these sections-

- Introductory Books for data science.
- Programming Books for Data Science
- Statistics Books for Data Science,
- Linear Algebra Books for Data Science
- Probability Books for Data Science
- Machine Learning books for Data Science.

**Introductory Books for data science**

This book covers almost all topics on Data Science-

**1.** **Data Science from Scratch**

**Author**– Joel Grus

**About Book**

As its name sound,” Data Science from Scratch”, so definitely this book is for beginners. This book starts from very basic. If you don’t have Python Knowledge, then also this is a good book for you.

As I have mentioned in Data Science Skills, knowledge of statistics, Linear Algebra, and Probability are mandatory. So this book will give you the **basics of linear algebra, statistics, and probability**. Along with that, you will understand how and when they’re used in data science.

The next skill for Data Science is Programming Language. So in this book, you will get a **crash course in Python. **

The next Skill for data science is Knowledge of Machine Learning. In this book, you will dive into the **fundamentals of machine learning.**

You will also learn how to implement models such as **k nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering. **

Knowledge of **Data Cleanin**g is also required for Data Science. In this book, you will learn how to **collect, explore, clean, munge, and manipulate data**.

In a nutshell, this book is an entry-level book for beginners.

**You Should Read this Book, If-**

- You are Beginner and don’t have any knowledge of Python or Statistics. Then you should definitely read this book.
- You want to learn the basics of Mathematics required for Data Science.

**Where To Buy-**

You can buy this book on Amazon- **Data Science from Scratch** or Download the Ebook **here**

#### **2. Data Science For Dummies **

**Author-** Lillian Pierson, Jake Porway

**About Book-**

**Data Science For Dummies** is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space.

This book focuses on Business cases. That’s why this book explains **big data, data science, and data engineering**, and how these three areas are combined to produce tremendous value. This book will help you to pick-up the skills you need to begin a new career or initiate a new project.

After reading this book, you will have background knowledge of **Big Data and Data Engineering.** You will also learn big data frameworks like **Hadoop, MapReduce, Spark, MPP platforms, and NoSQL**.

This book explains **machine learning and many of its algorithms. **You will also learn the evolution of the **Internet of Things**. This book also covers **data visualization techniques**.

**You Should Read this Book, if-**

- You are a beginner and want to learn everything related to
**big data, data science, and data engineering**.

**Where to Buy-**

You can buy this book on Amazon-**Data Science For Dummies** or download the Ebook from **here**

**3.** **Storytelling with Data **

**Author-**Cole Nussbaumer Knaflic

**About Book-**

Story Telling is the best way to teach something. This book is written in Story Telling format. **Storytelling with Data** uses graphics to understand the topics.

**Storytelling with Data** will teach you the fundamentals of data visualization and how to communicate effectively with data.

The author explains complex topics in a storytelling format. You don’t even realize that you understand complex topics easily.

After reading this book, you will learn about the context and audience. How to Determine the appropriate type of graph for your situation?.

After reading **Storytelling with Data**, You will think like a designer and utilize concepts of design in data visualization.

**You Should Read this book, if-**

- You want to get real-world experience in
**Data Visualization.**

**Where to buy-**

You can buy this book on Amazon- **Storytelling with Data**

**4. ** **Data Science from A-Z **

**Author-**Benjamin Smith

**About Book-**

This book explains all topics in a simple language. This book neither uses very technical words nor too plain. But the aim of this book is to cover concepts that might be otherwise misunderstood or easily ignored by the reader due to their inherent complexity.

In short, this book has all the necessary information a beginner level data scientist would have.

**You Should Read this Book, if-**

- You are a beginner in the Data Science field.

**Where to Buy-**

You can buy this book on Amazon- **Data Science from A-Z**

**Programming Books for Data Science**

Here, I will discuss some most popular books on Python and R for Data Science.

**5. ** **Python Data Science Handbook **

**Author-** Jake VanderPlas

**About Book-**

For Data Science, a programming language is mandatory. Python is the most suitable programing language for Data Science.

As a Data Scientist, most of the time you have to work on Data manipulation and Data Cleaning. You can perform all these tasks with Pandas.

With this handbook, you’ll learn how to use:

**IPython and Jupyter:**provide computational environments for data scientists using Python**NumPy:**includes the ndarray**Pandas:**features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python**Matplotlib:**includes capabilities for a flexible range of data visualizations in Python**Scikit-Learn:**for efficient and clean Python implementations of the most important and established machine learning algorithms

**You Should Read this Book, if-**

- You want to learn Python Libraries for Data Science.

**Where to Buy-**

You can buy this book on Amazon- **Python Data Science Handbook**

**6. R for Data Science**

Author- Hadley Wickham

**About Book-**

This book uses **R Programming Language** to perform tasks on Data science. R is also the most suitable programming language for Data Science. So, if you want to learn R instead of Python. Then this is the best book for you.

This book covers the basics of R for beginners in R. Along with that, **R for Data Science** covers more advanced topics.

In that book, you will learn-

- Exploration
- Wrangling
- Programming
- Modeling
- Communication

What I like about this book is that this book will not bore you. I found this book very interesting and an attention seeker.

**You Should Read this Book, if-**

- You want to learn Data Science with R.
- Beginners can also read this book.

**Where to Buy-**

You can buy this book on Amazon- **R for Data Science**

**7. Python for Data Analysis **

Author- Wes McKinney

**About Book-**

This book is good for analysts new to Python and for Python programmers new to data science and scientific computing.

This book will first teach you the **basics of Python programming**. Then it will cover Python’s role in data analysis and statistics. That’s why it is good for beginners in Python. After reading this book you can build real-world applications within a week.

** Python for Data Analysis** will also give you an idea when you start working as a Data Analyst or scientist.

You will learn basic and advanced features in **NumPy (Numerical Python).** Along with that, you will learn how to solve **real-world data analysis problems **with thorough, detailed examples.

**You should read this book, if-**

- You are analysts new to Python or Python programmers new to data science and scientific computing.

**Where to Buy-**

You can buy this book on Amazon-**Python for Data Analysis**

**Statistics Books for Data Science**

These are some best Books on Statistics for Data Science-

**8. An Introduction to Statistical Learning ( Statistic Book)**

**Author**– Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani

**About Book-**

As I have mentioned that **Statistical Knowledge** is required for Data Science. So, this book gives a good knowledge of Statistics. Like other statistical books focus on theory, but this book will explain practically.

This book is written for those people who don’t have programming and statistical knowledge. Even if you are an experienced person, you can refer to this book to brush up on your knowledge. Because of a lot of statistical concepts, you kind of forget about them over time.

This book presents some of the most important modeling and prediction techniques along with relevant applications. Topics include **linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering**, and more.

**You Should Read this Book, if-**

- You are a beginner in Data Science Field, or Experienced, who want to brush-up your knowledge.

**Where to Buy-**

You can buy this book on Amazon-**An Introduction to Statistical Learning**

**9. ** **Practical Statistics for Data Scientists **

**Author-**Peter Bruce

**About Book-**

If you are a beginner, then this book is good for you. **Practical Statistics for Data Scientists **explains how to apply various statistical methods to data science.

In this book, you will learn **randomization, sampling, distribution, sample bias**, etc.

All of these concepts are explained with examples. Along with that, this book explains how these concepts are relevant to data science.

This book will not only give in-depth knowledge but also good for getting a quick and easy reference to Data Science.

In short, this is a great reference book for Statistics in Data Science.

**Where to Buy this Book-**

You can buy this book on Amazon-**Practical Statistics for Data Scientists**

** Linear Algebra Book for Data Science **

#### **10. Linear Algebra Done Right **

**Author-** Sheldon Axler

**About Book-**

This is an undergraduate math book. As a Data Scientist, you should have knowledge of Linear Algebra. So in order to get the basics of Linear Algebra, this is the ideal book for you.

This book is not related to machine learning or programming knowledge. This is a pure Mathematics book that will give you all the basic details on **Linear Algebra**.

After reading this book you will learn inside and out how to do **matrices and how to handle the vector space and how to do pure math about high-dimensional spaces.**

**You Should Read this Book, if-**

- You want to get basic and in-depth knowledge of Linear Algebra. This book will cover all basics of Linear Algebra that are required for Data Science.

**Where to Buy-**

You can buy this book on Amazon- **Linear Algebra Done Right**

### **Probability Books for Data Science **

**11. ** **Introduction to Probability**

Author- Joseph K. Blitzstein, Jessica Hwang

**About Book-**

For Data Science, you should have basic knowledge of Probability. So, in order to learn the basics of Probability, this is the best book.

If you have studied probability in your school, then this is the best book to brush up on your knowledge. And if you never learn Probability, then this book will give you a **strong foundation in the core concepts**.

The book includes many **intuitive explanations, diagrams, and practice problems.** Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.

**Introduction to Probability** has been one of the most popular books for about 5 decades.

**You Should Read this Book, if-**

- You want to learn the basics of Probability for Data Science. This book is ideal for beginners and experienced.

**Where to Buy this Book-**

You can buy this book on Amazon- **Introduction to Probability.**

**12. Probability and Statistics for Data Science **

**Author-**Norman Matloff

**About Book-**

This book covers “**math stat**“―distributions, expected value, estimation, etc. In that book, Read datasets are used. All Data Analysis tasks are performed with the **R programming language.**

**Probability and Statistics for Data Science** Include many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks.

**Note- **You should have some knowledge of **calculus and programming** before reading this book.

**Where to Buy-**

You can buy this book on Amazon-**Probability and Statistics for Data Science.**

**Machine Learning books **

**13. Introduction to Machine Learning with Python **

**Author-** Andreas C. Müller, Sarah Guido

**About Book-**

This book will start your Machine Learning Journey in Python. In that book, you will learn the **fundamental concepts** and applications of machine learning. Along with that, you will learn A**dvanced methods for model evaluation and parameter tuning. **

This book also covers **Methods for working with text data, including text-specific processing techniques**.

**You should read this book, if-**

- You are a beginner in Machine Learning.
- Or you want to create a successful machine-learning application with Python and the scikit-learn library.

**Where to Buy-**

You can buy this book on Amazon- **Introduction to Machine Learning with Python.**

**14. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow **

**Author-** Aurélien Géron

**About Book-**

This book gives you a **hands-on approach to learning by doing**. It starts with the more **traditional ML approaches (the Scikit-learn part)** giving you a great deal of context and practical tools for solving all kinds of problems. This book has an excellent balance between theory/background and implementation.

This practical book shows you how even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data.

This Book uses concrete examples, minimal theory, and two production-ready Python frameworks—**Scikit-Learn and TensorFlow**.

The first part of the book explains basic **Machine Learning Algorithms. Support Vector Machine, Decision, Trees, Random Forests**, and many more. In this book,** Scikit-learn examples** for each of the algorithms are included.

In the second part, deep learning concepts through the **TensorFlow library** are explained.

**You Should read this book, if-**

- If you have basic programming knowledge.
- The one who is a beginner to Machine Learning and wants to start with the basics of coding.
- if you are interested in the popular scikit-learn machine learning library.

**Where to Buy-**

You can buy this book on Amazon- **Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow**

**15. ** **Python for Finance **

**Author-** Yves Hilpisch

**About Book-**

If you are in Finance and Data Science Field, then this book is a must-read for you. This book focuses on how to use Data Science tools to analyze the financial market.

**Python for Finance **is totally a practical book. I personally loved this book. And the reason is its practical approach.

This book covers important basics such as **NumPy, Pandas, and Time Series** as well as more sophisticated topics such as **machine learning and algorithmic trading strategies. **

**You Should read this book, if-**

- You want to analyze the financial market with Data Science tools.

**Where to Buy-**

You can buy this book on Amazon-**Python for Finance**

**Conclusion-**

In this article, you have discovered the **15 Best Books on Data Science.** Have you Bought or Read anyone of these Books?. If yes then tell your experience in the comment section.

I hope these **15 Best Books on Data Science** will help you to begin and boost your Data Science Journey.

Enjoy Learning!

All the Best!

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## Though of the Day…

–

‘It’s what you learn after you know it all that counts.’John Wooden

### Written By Aqsa Zafar

Founder of MLTUT, Machine Learning Ph.D. scholar at Dayananda Sagar University. Research on social media depression detection. Create tutorials on ML and data science for diverse applications. Passionate about sharing knowledge through website and social media.