Data Analytics Books: In this world of terabytes and petabytes of information/ data around which we are covered up, we all forgetting about the “Books”. As nowadays all the information is practically available on the google, SlideShare presentation and many more digital options. But we should not forget that books are always a universal source of knowledge and information. So books are special and it cannot be compared with anything else. One more fact is that books keep us focused and concentrated whereas in any other digital device you will be easily distracted.
So here we are going to enlist top 10 books on data science which every data scientist. Some of the books are technical that will interest programmers and analysts. The list can be utilised by the beginners as well as skilled professionals. There is a huge demand for the skilled data scientists, as we already posted about data scientist skills, responsibilities, salary, qualification. So if you don’t know about all this you can also go through this post. And today we are going to tell you best books of data science.
Top 10 Data Science Books
Check the collection below and choose the books according to your requirement. You can also buy the books as the links are also provided.
Must Read Books on Data Analytics
The author of this book is Viktor Mayer-Schonberger and Kenneth Cukier. The book examines the social impact of the data that is increasing rapidly and the way it is collected, stored and analysed. The book also provides practical toolkit to survive and thrive in Big Data World
The author of the book is Cathy O’Neil and Rachel Schutt. The publisher of the book is O’Reilly Media. If you are looking for a book that is based on the introduction to data analysis (science) then you must read this book. The book consists of the topics such as Algorithms, Logistic regression, Data visualisation, Data engineering and many more topics.
The author of the book are Foster Provost and Tom Fawcett and publisher is O’Reilly Media. The book is about the problems that arise in real time world business and what you can do to tackle them.
The authors of the book are John Myles White and Drew Conway. The book is ideal for the programmers from any of the background like the business, academic research and government.
Nate Silver is the author of the book and the publisher of the book is Penguin Group. Nate Silver is known to be as nation’s foremost political forecaster. He has written this book that highlights the mistakes and failures that is due to so many predictions and what can be done to correct them.
6. R Cookbook
The author of this book R Cookbook is Paul Teetor. If you want to learn R language and you are a beginner then this book is surely going to help you. Also if you are a professional programmer then also this book is going to help you, it will revive your memory and will expand your horizons.
The author of the book is Russell Jurney. The books provide knowledge of effective analytics application with Hadoop. This book will change your approach and will change the way you do analysis till now depending upon the data.
The authors of the book are Ian H. Witten, Eibe Frank, and publisher is Morgan Kaufmann. The book provides information on machine learning, its tools and techniques as well as techniques.
The author of the book is Toby Segaran and Robert Romano. In this book, you will find opportunities and challenges that are involved in working with huge amount of datasets that are made available on the web and also learn how to visualise the trends in urban crime and data mashups.
The author of the book is Christopher Stener and publisher is Portfolio Hardcover. In this book, Christopher Stenir is trying to tell how algorithms took over and also why “bot revolution” is about to spill into each aspect of our lives.
So these were the top 10 Best Data Science Books that can be read by both beginner and skilled professionals. If you want to have some other information about the field you can leave a comment below and we will reply to you at the earliest.