Data science can be a challenging field, which is why it’s important for you to decide on which textbooks are going to be the best options to help you advance your knowledge on this topic. Whether you are just interested in this topic, want to get started in this industry, or have some skills already in this industry, there are plenty of options for books. The textbooks listed here are ranked based on your readiness level, to help you build upon whatever foundation you had currently.
For Those with General Interest in This Topic
If you have a general interest in data science, you want something that covers a lot of the basics as well as offers a variety of valuable insights. This section will take a look at the best data science general interest books.
“Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are” by Seth Stephens-Davidowitz
One of the reasons this is the best book on data science is that this isn’t a technical book. This means that everyone can read it and understand the basic concepts of the book. Even more interestingly, the book engages the attention of the audience by offering captivating storytelling that perfectly illustrates a specific data science concept. These stories cover people who are being extremely creative and find patterns in seemingly random things. The fact is that these seemingly random things can reveal a lot more than you think they can.
That’s what this book is about. Everybody lies, but by using data you can easily find the truth. This book was made for people who are not only curious about what data science is, but also what it’s capable of doing. This is especially true when it comes to social data. It’s a fun and interesting read for those who have a basic interest in the topic.
“Algorithms of Oppression” by Safiya Noble
Using very simple stories, this author explores the topic of small data with so much context. It offers a unique perspective on data science than many other similar data science general interest books. For instance, the author discusses how she was organizing a party for her own niece and friends. In this story, she recalls how she Googled something like “black girls” on Google and ended up finding inappropriate results. The same happened when she searched for “Asian girls” and “Latina girls”.
She goes on to explain how Google is based off of a revenue model, so their search results are the ones that are the most profitable for them. The book goes into further detail about this and other topics, offering an often sobering look at data science.
Textbooks for Beginners
If you are just starting out or just have some basics under your belt, you want a book that can help you build upon these fundamentals. This section will take a look at a couple of the best textbooks for beginners.
“An Introduction to Statistical Learning: with Application in R” by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
A major problem that people have with textbooks for beginners is that data science textbooks are unreadable for beginners. These textbooks may offer a lot of valuable information, but there was no show of the application of these theories. That’s why this book is so great. While it may not be quite as in-depth as other textbooks, you get a lot of knowledge that you would need to be successful as a data scientist. You can learn some of the essential machine learning algorithms, giving you the statistical knowledge that you need to know what’s going on in those black boxes where data goes in and out.
This particular book is created for people who don’t have statistics or programming in their background. However, that doesn’t mean that you can get any valuable information from this book if you do have experience in data science. This is a great refresher for more advanced data scientists and a great starting point for those who are beginning to learn about data science.
Textbooks for Advanced Data Scientists
Finally, for those more advanced professionals in data science, this textbook can be a great investment.
“Pattern Recognition and Machine Learning” by Christopher M. Bishop
As far as textbooks go, this is one of the best-advanced data science textbooks. This book is based on the Bayesian viewpoint. As soon as you read the first few pages of this, you can clearly see that this isn’t for a beginner. This book is one that is very highly regarded by data scientists, one that some of the top experts in this field constantly talk about.
So, what does this book mean when it says, “pattern recognition”? When it comes to machine learning, it all comes back to pattern recognition, doesn’t it? Machine learning is a pretty fancy term that basically means you are using old data in order to think about new data that hasn’t been seen previously. This is such a great book as it covers so much information on data science, which can offer you a fresh new perspective on the topic. It gives such in-depth information and clearly presents the topic in a manner that thoroughly covers the important concepts of advanced data science. It’s definitely not a book for beginners.
Conclusion
If you are looking for a great textbook on data science, these are all some of the best options that you can choose from. No matter which stage of knowledge you have in data science, these are the best options no matter what your readiness level is. Even if you are a more advanced data scientist, any of these book options can be great ones to consider for your collection. These books can offer you valuable inside and incredible information on data science, with applications that you can take to improve your skills. These are just some of the must-haves that you should invest in.