In addition to the fact that data science is one of the highest paying and most popular fields today, it’s also important to keep in mind that it will continue to be more innovative and challenging for another decade or more. there will be enough data science jobs that can bring you a good salary, as well as opportunities to grow.
That said, there’s nothing better than reading data science books to get going.
You are reading: Best data science books
Learning data science through books will help you get a holistic view of data science as data science is not just about computation but also includes math, probability, statistics, programming, learning automatic and much more.
data science books
These are some of the best books you can read to better understand data science concepts:
1. head first statistics: a brain-friendly guide
Like other headfirst books, the tone of this book is friendly and conversational, and it is the best book to start with data science. The book covers a large number of statistics starting with descriptive statistics (mean, median, mode, standard deviation) and then continues with probability and inferential statistics like correlation, regression, etc. If you were a science or commerce student in school, you may have studied it all, and the book is a great start to brush up on everything you’ve already learned in detail. there are a lot of pictures and graphics and bits on the sides that are easy to remember. you can find some good real-life examples to keep you hooked on the book. Overall, it’s a great book to start your data science journey.
You can buy the book here.
2. practical statistics for data scientists
If you’re a beginner, this book will give you a good overview of all the concepts you need to learn to master data science. the book is not too detailed but it gives good enough information on all the high level concepts like randomization, sampling, distribution, sample bias, etc. Each of these concepts is well explained and there are examples along with an explanation of how the concepts are relevant to data science. the book also surprises with a survey of ml models.
This book covers all the topics necessary for data science. it is a quick and easy reference, however, it is not enough to master the concepts in depth since the explanations and examples are not detailed.
You can buy the book here.
3. introduction to probability
if you have a background in math in school, you might remember to calculate the probability of getting a spade or a heart from a pack of cards, etc.
This is perhaps the best book to learn about probability. the explanations are quite neat and resemble real life problems. If you have studied probability in school, this book is a must to expand your knowledge of the basic concepts. If you’re learning probability for the first time, this book can help you build a solid foundation in the basics, though you’ll have to do a little more work with the book.
The book has been one of the most popular books for about 5 decades and that’s one more reason why it should definitely be in your library.
You can buy the book here.
4. introduction to machine learning with python: a guide for data scientists
this is a book that can help you start your ml journey with python. the concepts are explained as for a layman and with enough examples for a better understanding. the tone is friendly and easy to understand. ml is quite a complex subject, however after practicing along with the book you should be able to build your own ml models. you will get a good understanding of ml concepts. The book has examples in Python, but you don’t need any prior knowledge of math or programming languages to read this book.
This book is for beginners and covers basic topics in detail. however, reading this book alone will not be enough as you delve deeper into ml and coding.
You can buy the book here.
5. python machine learning for example
As the name suggests, this book is the easiest way to get started with machine learning. The book helps you get started with Python and machine learning in a detailed and interesting way with some elegant examples like spam detection using bayes and predictions using regression and tree-based algorithms. the author shares his experiences in the various areas of ml like ad optimization, conversion rate prediction, click fraud detection, etc. which adds wonderfully to the reading experience. /p>
although the book covers the basics of python, you may want to start the book after you get some basic knowledge of python. The book will guide you through the process of setting up the necessary software through creating, updating, and tracking your models. All in all, a great book for both beginners and advanced users.
You can buy the book here.
6. pattern recognition and machine learning
This book is for all age groups, whether you are an undergraduate, graduate or advanced level researcher, there is something for everyone. If you have a Kindle subscription, this book will cost you nothing. get the international edition that has colorful images and graphics that make your reading experience worthwhile.
Content-wise, this is a book that covers machine learning from the inside out. He is thorough and explains concepts with examples in a simple way. Few readers may find some of the terms difficult to understand, but you should be able to do so using other free resources like web articles or videos. the book is a must if you are serious about machine learning, especially the mathematical part (data analysis) is exhaustive by nature.
Although you can use the book for self-study, it would be a better idea to read it alongside some machine learning courses.
You can buy the book here.
7. python for data analysis
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True to its name, the book covers every possible method of data analysis. It’s a great start for a beginner and covers the basics of Python before moving on to Python’s role in data analysis and statistics. the book is fast paced and explains everything in a super simple way. you can create some real apps within a week of reading the book. This book can also provide you with a guide or reference for topics that you might otherwise miss when looking for online courses.
With a focus on learning Python and data science, this book gives you a clear idea of what you can expect as a data analyst or data scientist when you really start working. The author also gives many references in the book and points out helpful resources that you might like to read. overall, a well organized book with a detailed explanation of data analysis concepts.
You can buy the book here.
8. bare stats
This book brings out the beauty of statistics and brings statistics to life. the tone is witty and conversational. You won’t get bored reading this book or feel the heaviness of math! the author explains all statistics concepts – basic and advanced with real life examples. The book starts with very basic things like the normal distribution, the central theorem and continues with complex real life problems and correlation of data analysis and machine learning.
Although the book explains the basics well, it will be good to have some background in statistics with some of these courses, so you can get on with the book quickly.
You can buy the book here.
9. data science and big data analytics
This book introduces big data and its importance in today’s digitally competitive world. The entire data analytics life cycle is explained in detail along with a case study and engaging visuals so you can see how the whole system works in practice. the structure and flow of the book are very good and well organized. you can easily understand the full overview of how the analysis is done, as each step is like a chapter in the book. The book includes clustering, regression, association rules, and much more along with simple, everyday examples you can relate to. The reader is also introduced to advanced analytics using mapreduce, hadoop, and sql.
if you plan to learn data science with r, this is the book for you.
You can buy the book here.
10. r for data science
another book for beginners who want to learn data science using r. r with data science explains not only the concepts of statistics, but also the type of data you would see in real life, how to transform it using concepts like median, average, standard deviation, etc. and how to plot the data, filter it and clean it. it’s. the book will help you understand how messy and raw the actual data is and how it is processed. Data transformation is one of the most time consuming tasks and this book will help you gain a lot of knowledge about the different data transformation methods for processing so that significant insights can be gained from them. If you want to learn R before starting the book, you can do so with simple online courses; however, the book covers enough of the basics to get you started right away.
You can buy the book here.
additional data science books
Here are some more good books you might be interested in:
11. turning point
This is not a technical book. However, since you have decided to move on to a data science career, you will need to know why data science and big data hold such an important place today. the book is written from a business perspective and offers a lot of insights on how all the technologies like cloud, big data, it, mobility, infrastructure and others are transforming the way businesses work today along with interesting stories and personal experiences to share. the changing times and how we must deal with them are wonderfully described in this book.
is a good read and will keep you motivated throughout your data science learning journey.
You can buy the book here.
12. narration with data
Anything that is told as a story and displayed as graphics fits easily into our minds and stays there permanently. the book is quite impressive and covers the fundamental concepts of data visualization so that you understand how to make the most of the vast amount of data available in the real world. The author’s way of explaining each concept is totally unique as he tells it in the form of a compelling story. You wouldn’t even realize how many concepts you can grasp in a day of reading the book: knowing the context and audience, using the right graphic for the right situation, recognizing and removing clutter to get only the important information, using the most important parts of the data and present them to users: all this and more.
You can buy the book here.
13. big data: a revolution
This is a must-have book, an introduction to your journey through big data, data science, and artificial intelligence. It’s not a technical book, but it will give you a comprehensive insight into how big data is captured, converted, and processed into sales and profits, even without users like us knowing about it. explains how companies use our data and the information we share over the internet is used to create new solutions and business innovations that make our lives easier and connect us all. it also talks about the risks and implications of doing so, and how security measures are put in place to prevent data breach or misuse. there are technical documents at the end that are quite useful. a good and easy read for all.
You can buy the book here.
14. practical data science with r
This is a mid-level book, a good balance of basic principles and advanced principles of data science. the sharp focus is on business demands, which is what makes the book very practical and interesting. it also goes into great detail about statistics, which is one of the fundamentals of data science. most books simply explain how things are done; this book explains how and why! that helps motivate readers to get into deep learning and machine learning. this is a good book for both beginners and advanced level data scientists. it gets more difficult as the topic progresses, but you can follow most of the book easily.
You can buy the book here.
15. the data science handbook
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This is an advanced book. If you have some knowledge about statistics and data science through other books or tutorials, you will appreciate the content of the book. It is not a purely technical book, but rather a quick reference, as it contains information in the form of questions and answers from several leading data scientists. The questions flow in an organized way and help you understand every aspect of data science, such as data preparation, the importance of big data, the automation process, and how data science is the future of the digital world. however, the book lacks real case studies, however if you are business minded you will learn a lot of strategies and advice from renowned data scientists who have been there, done that.
You can buy the book here.
16. business analytics: the science of data-driven decision making
This is an impressive and detailed book that explains the theory and practical applications to give you a complete understanding. The author deals with the topics subtly and presents many case studies that are easy to understand, understand and follow. The book has everything from economics, statistics, finance, and everything you need to start learning data science. the book has been written with a lot of effort and experience and the way the ideas have been presented shows the same. it includes statistical and analytical tools, machine learning techniques, and amalgamates basic and high-level concepts very well. you will also learn about school models and six sigma towards the end of the book.
You can buy the book here.
17. data mining techniques
a wonderful book that explains data mining from scratch. so much so, that you don’t have to be a computer science graduate to understand this book. starts by explaining about the digital age, data mining, and then goes on to explain the types of data that can be mined, the patterns that can be mined, for example cluster analysis, predictive analytics, correlations, etc., and the technologies that are used: statistics, machine learning and database. the book is purely technical and you can go step by step to fully enjoy the book. the book is detailed, essential in your collection.
has many basic and advanced techniques for classification, cluster analysis, and also talks about trends and ongoing research in the field of data mining.
You can buy the book here.
18. think with data
This is a small book that can be read alongside other reading materials and online courses. it provides a wealth of useful information and enables critical business thinking in the reader. it helps you understand why things are happening the way they are. Through the chapters, you’ll learn how to ask good meaningful questions, write down the important details of an idea, and get key information to focus on. covers data-specific reasoning patterns very well. the book will help you think “why” and not just “how”. It covers what is called convo: context, needs, vision and result.
You can buy the book here.
19. machine learning with pyspark
The book covers machine learning models, nlp (natural language processing) applications, and recommender systems using pyspark in detail. helps you understand real-world business challenges and solve them. covers linear regression, decision tree, logistic regression, and other supervised learning techniques. This book will greatly enrich your knowledge, especially if you not only read it, but work with the book and practice. You’ll also appreciate pyspark’s rich libraries that are ideal for machine learning and data analysis. a great book to learn how to use recommendation systems using spark – clean and simple.
You can buy the book here.
20. generative deep learning
The book is like any other fiction book that keeps you hooked until the last page. If you’ve read Harry Potter, you’ll know what we’re talking about. the author has done an outstanding job of writing all the concepts in the form of stories that are easy to understand. otherwise, the topics of statistics and intuitive learning are a bit dry, and this book does its best to make it as interactive and engaging as possible. if you read other books, you will realize how complex neural networks and probability are. this book makes it simple. Before starting the book, familiarize yourself with Python through some courses or tutorials. one of the best books on deep learning techniques from scratch.
You can buy the book here.
21. data science for companies
Purely business oriented, this is a book to start with if you can’t make up your mind in the field of data science. clearly explains why you should learn data science and why it’s the right choice for you. there are beautiful examples like recommendation system, telecom churn rate, automated stock market analysis and more. the book keeps you motivated. however, it is not a book that will preach. it’s handy and gives you enough references to get you started on your technical journey as well. the book emphasizes discovering new business cases rather than just processing and analyzing data.
see a preview of the book on amazon to see the concepts that are taken up in the book.
You can buy the book here.
22. design data-intensive applications
Last but not least, this book helps to understand the architecture of today’s data systems and how they can be adapted to data-driven and data-intensive applications. It doesn’t delve into administration, security, installation, and other things, but it does go into detail about data recovery, database systems, and fundamental concepts. this book is for you if you are an architect. the author discusses various aspects of database design and data solutions and also provides many other resources (at the end of each chapter!) to help you further your knowledge on the subject.
You can buy the book here.
more to go…
There are hundreds or more books related to data analytics and data science and don’t be overwhelmed with the sheer number of books. you don’t have to read them all. We’ve carefully selected them, and you should be able to build real-world models and gain a deep understanding of data science with these books and the other resources mentioned in the blog. Some more reference books that may be helpful are Learning SQL, Too Big to Ignore, The Hundred Page Machine Learning Book, Communicating Data with Tableau, and Accessible Data Analysis. Start your data science journey with any of our 22 suggested books and let us know if you enjoyed reading them.
If you want to be an expert in data science, then the Data Science Course: The Complete Data Science Crash Course may be a great advantage for you.
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