# Best Data Science Books for 2020 to Become A Data Scientist

Data Science has established its roots in the business world in the last few years.

Almost all the leading organizations are looking for Data Scientists and are providing high paid salaries too.

It’s increasing **popularity** and **demand** have created interest in a lot of people for learning Data Science.

Many people dream about becoming a Data Scientist but are actually confused about how to start.

In this tutorial, we will explore some of the very useful Data Science books which will help you throughout your journey from a beginner in Data Science to a master of Data Science.

### Concept of Data Science

What is a Data Science? Data Science is a very vast field.

It is generally the study of data by performing various operations on the data to extract some meaningful insights from it for making a decision.

This analysis of data requires a combination of various skills such as **statistics** and **probability**, **machine learning**, **programming**, etc.

Let us first understand how these skills are important in Data Science.

**1. Statistics** and **Probability** are the key components of Data Science.

Data Science is all about extracting meaningful insights from the data and this is done by applying various probabilistic and statistical approaches.

If you are planning to learn Data Science then you must first have a good understanding of both statistics and probability.

Statistics and probability are the part of mathematics and are used for **analyzing** large data sets, identifying various patterns and trends in the data by applying several mathematical computations on the data and finally predicting the results.

**2.** **Machine** **Learning** can be considered as a part of Data Science.

When the dataset is so large that it becomes difficult for a Data Scientist to handle it using statistical and probabilistic approaches, then Machine Learning comes to the rescue.

Machine Learning is used for more **complex** problems.

In such problems, Statistics is used for extracting the **insights** and Machine Learning **algorithms** are then used for predicting the final results based on these insights.

Data Science provides the solution to problems by using some Machine Learning algorithms.

Now let’s see the best Data Science books which you should refer to become a Data Scientist.

## Data Science Books

The following books will help you to explore each and every aspect of Data Science.

### 1. Python Data Science Handbook

This book is written by **Jake** **VanderPlas** which is best suited for those who are beginners in the Data Science field.

The book starts with the very basics and provides you a deep knowledge of each and every topic covered in it in such a way that you can apply it to your problems and master Data Science.

If you are familiar with the Python programming language and want to learn how to apply Data Science using **Python**, then this book will not disappoint you.

This Data Science book helps one to get started with Data Science using Python.

Python Data Science Handbook includes a basic Introduction to Python Language along with how to apply Machine Learning algorithms using the Python-based tools.

This book covers the need for the whole Data Science process starting from collecting the data, analyzing it, extracting information and visualizing the results*.*

The book introduces various Python tools available for doing Data Science.

Some of these tools are **IPython**, **Numpy**, **Panda**, **Matplotlib**, and **ScikitLearn**.

### 2. Data Science for Dummies

This Data Science for Dummies’ book is written by **Lillian** **Pierson**.

In today’s era of Big Data, the demand for professionals in the Data Science field has been accelerated but due to the significant gap between demand and skill.

There are very few people who have the skills to fill this increasing **position** of responsibility.

This Data Science book provides a perfect beginning for the IT professionals and the students working on Data Science, who wants to apply their findings in solving real-world problems.

If you want to know about the skills and tools for initiating a new project then this Data Science book will help you to understand the **programming languages**, **technologies**, and the **mathematical** methods that you need to focus on.

The book provides an overview of the fields like **Big Data**, **Data Science** and **Data Engineering**.

It demonstrates how these areas work together for adding tremendous value to the products.

It introduces some of the frameworks of Big Data like **Hadoop**, **MapReduce**, **Spark**, **MPP platforms**, and **NoSQL**.

In addition to these frameworks, the book also provides the details of certain data visualization techniques.

### 3. R for Data Science

This Data Science book is written by **Hadley** **Wickham** and **Garrett** **Grolemund**.

It will help you to get started with Data Science in no time and also does not require any previous knowledge of programming.

This book will teach you how to apply the Data Science concepts using **R** and transform the raw data into useful insights and visualize the results.

The R for Data Science book provides you with the introduction to R, RStudio, and various packages in R that are devised for applying Data Science with ease and fun.

For doing Data Science effectively, certain skills are required and this Data Science book provides you with the best practices in R.

You will learn the best practices to **clean** your data and **transform** it into a form that it becomes more convenient to analyze it efficiently and model it.

### 4. Storytelling with Data

It is written by **Cole** **Nussbaumer** **Knaflic**.

This book can be referred by anyone who is working in the field of Data Science at any level of experience.

When someone explains us something in the form of a story or some graphics, we can retain it for a longer time.

This book teaches you the fundamentals of data **visualization** in a much similar way.

The book not only teaches you the data but tells a story with it which will help you to understand how to communicate **effectively** with data.

Storytelling with Data is a book that will help you to understand, the audience in every possible way.

How to choose an appropriate visual display, how to identify and remove the elements which do not add or remove any informative value to or from your visuals.

This Data Science book will make you think like a designer and tell a story with the data which is a magical way to **engage** your audience and communicate effectively with the data.

### 5. Big Data – A Revolution That Will Transform How We Live, Work and Think

If you are planning to learn Data Science, then this book by **Viktor Mayer-Schonberger, Kenneth Cukier** is a must-read book for you, because Big Data lies at the core of Data Science.

The term Data Science came into the picture because of the lack of resources to handle the immeasurable amount of data generating with each passing day.

The book is very simple to read and can be used by everyone.

This Data Science book does not get into many **technical** details and does not require any prerequisites but tells us how big data is a reason for remarkable changes in the business world.

The book provides you an understanding of how the leading companies and organizations are using our data which we share through the internet, for solving many **business** problems and to connect with all of us.

It also tells about the risk involved in all this and the security measures that are taken to protect your data from any kind of misuse.

### 6. Head First Statistics: A Brain-Friendly Guide

This book is written by **Dawn** **Griffiths** and is best suited for absolute beginners in statistics.

Whether you are a student or a professional or just someone who wants to learn **statistics**, then this Data Science book is a must-read for you to start your journey in statistics in a very interactive, exciting and fun way.

The book teaches you everything that you need to know about statistics.

This book is full of **puzzles**, **stories**, **visual aids**, and real-world examples and makes you familiar with each and every approach of statistics.

The Head First Statistics book will not only help you to master statistics but also teaches that how it works in the real world.

### 7. Introduction to Probability

The book Introduction to Probability is written by **Charles M. Grinstead**.

This book can be preferred by university students or by anyone who is a beginner in probability.

The book includes an **introductory** course on probability.

This Data Science book demands no other prerequisites expect some basic mathematical concepts such as multiple integrals, calculus.

The book introduces all the ideas and techniques of the field.

It covers various concepts such as **discrete probability distributions**, **conditional probability**, **continuous probability densities**, etc.

The book includes over 600 exercises for practical purposes and gives you the opportunity to understand how to apply it to real-life problems.

### 8. A Probabilistic Theory of Pattern Recognition

This book is written by **Luc Devroye** and can be used by people working in the research field as well as by students for keeping their probabilistic knowledge up to date.

Pattern Recognition is the process of applying Machine Learning algorithms on the dataset to identify various trends and patterns existing in the data which is proved to be a very **challenging** task.

To solve this problem various approaches have been proposed.

This book introduces the **probabilistic** analysis of these approaches.

The book provides the details of various concepts related to distance, parametric as well as **non-parametric** approaches for classification which are based on kernels and nearest neighbors, neural networks and much more.

This Data Science book includes over 430 problems and exercises for practice that will help you better understand the concepts.

### 9. Think Stats

This Data Science book is written by **Allen B. Downey**.

If you have the knowledge of programming and know how to apply various tools from statistics and probability on data to extract information, then this book is for you.

It provides you with a brief introduction about how to perform statistical analysis through programming instead of doing **calculations manually** with the help of programs written in python.

This book will help you to develop a better understanding of statistics and probability by writing and testing programs and how you can use it for answering questions to real-world data.

Throughout this book, you will work with a **case** **study** that will help you to understand the entire data analysis process in detail, that is, collecting data and how to apply statistics for identifying patterns and testing the results.

### 10. Introduction to Machine Learning with Python: A Guide for Data Scientists

This book is written by **Andreas Muller** and is best suited for beginners who want to learn how to apply Machine Learning algorithms to various problems using Python.

It provides an introduction to the **fundamental** concepts from the very basic level as well as various applications of Machine Learning in our daily lives.

The book focuses more on the implementation of the Machine Learning algorithms practically rather than the math and statistics behind them.

It teaches you that how you can build a successful Machine Learning applications, using **Python** and the **scikit-learn** library.

This Data Science book will also help you a lot to improve your Data Science skills and become a good data scientist.

### 11. Mathematics for Machine Learning

This book is written by** A. Aldo Faisal**, **Cheng Soon Ong**, and **Marc Peter Deisenroth**.

One needs to have a good knowledge of mathematics for jumping into the field of Machine Learning.

If you are a newbie to Machine Learning then this book will be perfect for you to step in the field of Machine Learning by learning the basic mathematical tools required in Machine Learning.

The book teaches you the fundamental mathematics tools such as **linear algebra**, **vector calculus**, **optimization**, **probability**, and **statistics**, etc.

This Data Science book tries to fill the gap between the mathematical tools and Machine Learning algorithms.

The book also contains a number of examples and practice problems after every chapter to test your practical knowledge.

### 12. The Hundred-Page Machine Learning Book

If you have no previous knowledge of Machine Learning then this book written by **Andriy Burkov** will provide you with just the right amount of detail to get you started and have a comfortable level of understanding about the field.

This is a very unique book that compacts everything you need to about Machine Learning in just a hundred pages.

Despite its short length, the book contains all the important aspects of Machine Learning without any loss of **quality**.

The Hundred-Page Machine Learning book contains only those parts from the vast field of Machine Learning that are really significant in practical applications.

The book is not very easy to read because each and every word of the book holds great **value** and **information**.

It also provides an introduction to the technical and mathematical background of Artificial Intelligence.

The book also illustrates some of the Machine Learning algorithms using the Python programming language.

## Summary

The right guidance and resources will help you to learn the details of all areas of Data Science.

In this tutorial, we have explored the best Data Science books that will help you to gain an** in-depth** knowledge of the different skills required for doing Data Science.

Reading these Data Science books will help you to ace the field and master the technology to become a Data Scientist.