Top 10 Bestselling Data Science Books

Top 10 Bestselling Data Science Books for 2019

Today We will discuss some amazing best selling Data Science books for Beginners, Intermediate and Undergraduate computer science students. So let's explore Top 10 Bestselling Data Science books.

Top 10 Bestselling Data Science books are

1. Data clysm: Who We Are (When We Think No One's Looking)

Data clysm book by Christian Rudder

Author: Christian Rudder

Basic Information of this Book:

Our personal data has been used to spy on us, hire and fire us, and sell us stuff we don’t need. In Dataclysm, Christian Rudder uses it to show us who we truly are. 

For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become new demographers.

In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.

2. The Visual Display of Quantitative Information

The Visual Display of Quantitative Information book by Edward R Tufte

Author: Edward R. Tufte

Basic Information of this Book:

The classic book on statistical graphics, charts, tables. Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with a detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. 

This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

3. Data Science for Dummies

Data Science for Dummies book by Lillian Pierson

Author: Lillian Pierson

Basic Information of this Book:

Not surprisingly, this book is a fantastic starting point for anyone seeking to pick up this skill. It gives a quick overview of all things data science, with a broad focus on a variety of business cases, giving you a good idea of what to expect when making use of your budding company’s databases. This textbook-like resource will help you decide whether your startup could benefit from further exploration of data, even going down into the details of which type of analysis can be applied to certain business cases.

4. The Art of Data Science

The Art of Data Science book by Roger D Peng

Author: Roger D. Peng

Basic Information of this Book:

It can be tough for some to view data analytics as anything other than a rigid and difficult-to-acquire skill, given its focus on fundamental knowledge of mathematics and statistics. However, in reality, not only can the interpretation of data produce a wide range of useful business insights, but the very analysis of data is much more commonsensical than you might expect.

5. Data Analytics Made Accessible

 Data Analytics Made Accessible book by Anil Maheshwari

Author: Anil Maheshwari

Basic Information of this Book:

The topic of data science can often be dense, locked behind walls of chunky and unreadable text—but not with this data science textbook. Concise and conversational, this is an easy read that is still filled to the brim with important knowledge, notably the concrete real-life case studies displaying how the science can be applied in business situations. It even includes a short R tutorial. This particular edition also gives some valuable insights and suggestions based on the response of reviewers of previous editions, making for an updated and modern view of the advancements in data science.

6. Numsense! Data Science for the Layman: No Math Added

Numsense! Data Science for the Layman: No Math Added book by Annalyn Ng

Author: Annalyn Ng

Basic Information of this Book:

Everyone has to start somewhere, and this book on data science is perhaps the best way for a layman to get some knowledge of the industry and the science itself. This book promises an absence of math, a gargantuan task in the algorithm-based industry. However, by dedicating each chapter to the works of every important algorithm in data science, it allows for a very practical understanding of the knowledge that will require later on in your journey.

7. Lean Analytics: Use Data to Build a Better Startup Faster

Lean Analytics: Use Data to Build a Better Startup Faster book by O'Reilly

Author: O'Reilly

Basic Information of this Book:

Whether you’re a startup founder aiming to disrupt an industry or an entrepreneur hoping to bring change from within, this book can help you by teaching the right way to take your business from initial idea to market, through the use of analytics and data.

8. Doing Data Science

Doing Data Science book by O'Reilly

Author: Rachel Schutt and Cathy O'Neil

Basic Information of this Book:

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.

In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.

9. The Functional Art: An Introduction to Information Graphics and Visualization

The Functional Art: An Introduction to Information Graphics and Visualization book by Alberto Cairo

Author: Alberto Cairo

Basic Information of this Book:

 In this practical introduction to understanding and using information graphics, you'll learn how to use data visualizations as tools to see beyond lists of numbers and variables and achieve new insights into the complex world around us. Regardless of the kind of data, you're working with business, science, politics, sports, or even your own personal finances-this book will show you how to use statistical charts, maps, and explanation diagrams to spot the stories in the data and learn new things from it.

10. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management

Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management book by Michael Berry

Author: Michael J. A. Berry and Gordon S. Linoff

Basic Information of this Book:

Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems. Each chapter covers a new data mining technique and then shows readers how to apply the technique for improved marketing, sales, and customer support. The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining. More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining. Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis.

So that's it for today. We will meet with a new collection of Data Science Books and other resources very soon. We hope these books will help you.

For more updates, stay tuned with us on LunaticAI.

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