10 Must Read Books for Data Scientists
Blog: GestiSoft
With a huge amount of information pouring from the different resources, it becomes convenient for people to read a blog, watch a tutorial video online, Slideshare etc to uplift their data skills. With so many resources available online, now the question is Do we still need books? The answer is always yes, books keep you interested and focused, no irritating ads, pop-ups, no distractions, just learn & grab new information. Seizing information from online sources is a must, but learning from books is still special. There is a huge content written on Data science and it’s not easy to figure out the best out of them, but still we’ve come with this list of 10 Must Read Books for Data Scientists that one should have on their shelves.
The list is prepared by considering the needs of both beginners and skilled professionals, so what are you waiting for. Get them, find a relaxing place, good reading glasses, and dive into the sea of data science information. With the huge amount of data pouring from all the sectors of life, the demand for skilled data scientists has increased.In fact, the demand is outstripping the supply. So, it is necessary to upgrade your skills with the new technologies that are coming up to keep yourself ahead in the game. Let’s get started now.
10 Must Read Books for Data Scientists
Check out the collection of some informative books written with a purpose to make readers more familiar with the aspects of Data Science, Data Mining, Machine Learning, Data Science Tools, and Programming Languages for Data Science. Pick the book as per your requirement and area of interest, the purchase link is also provided so that you don’t have to struggle to get the book.
Note: We’re sharing this post just to let readers pick the best book available. By no means, we’re advertising any author or brand here. The order by which books are shown is random, we’re not providing any ranking here.
1. Big Data A Revolution That Will Transform How We Live, Work, and Think
Authors: Viktor Mayer-Schonberger and Kenneth Cukier
Publisher: Jenna Dutcher (2013)
Purchase Link: Buy Now
In this book, two of the most popular data experts Viktor Mayer-Schonberger and Kenneth Cukier explained the various intricacies of big data. Must read for data lovers looking to explore the reality of a big data world.
2. Doing Data Science: Straight Talk from the Frontline
Author: Cathy O’Neil and Rachel Schutt
Publisher: O’Reilly Media
Purchase Link: Buy Now
Look for an idea introduction of Data science? Then, this is the book you must read, the following topics are covered in the book
- Statistical inference, exploratory data analysis, and the data science process
- Algorithms
- Logistic regression
- Spam filters, Naive Bayes, and data wrangling
- Financial modeling
- Data visualization
- Social networks and data journalism
- Recommendation engines and causality
- Data engineering, MapReduce, Pregel, and Hadoop
3. Data Science for Business
Author: Foster Provost, Tom Fawcett
Publisher: O’Reilly Media
Purchase Link: Buy Now
Through this book, you’ll get to know the problems that arise in real- world business and how you could think data analytically to tackle them. Foster Provost and Tom Fawcett has written this book, published by O’Reilly Media.
4. Machine Learning for Hackers
Authors: Drew Conway & John Myles White
Publisher: O’Reilly
Purchase Link: Buy Now
Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.
5. The Signal and the Noise: Why So Many Predictions Fail – But Some Don’t
Author: Nate Silver
Publisher: Penguin Group
Purchase Link: Buy Now
Nate Silver who is considered as the nation’s foremost political forecaster has written this book to highlight the mistakes behind the failure of so many predictions and what you need to follow to be an accurate forecaster.
6. R Cookbook
Author: Paul Teetor
Publisher: O’Reilly Media
Purchase Link: Buy Now
If you’re a beginner in R- Language the R Cookbook will help get you started. Learn what you need to do statistical work. If you’re an experienced data programmer, it will jog your memory and expand your horizons.
7. Agile Data Science: Building Data Analytics Applications with Hadoop
Author: Russell Jurney
Publisher: O’Reilly Media
Purchase Link: Buy Now
This book will teach you how to build an effective analytics application with Hadoop. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing, depending on what the data is telling you.
8. Data Mining: Practical Machine Learning Tools and Techniques
Author: Ian H. Witten, Eibe Frank
Publisher: Morgan Kaufmann
Purchase Link: Buy Now
This book offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations.
9. Beautiful Data: The Stories Behind Elegant Data Solutions
Author: Toby Segaran ,Robert Romano
Publisher: O’Reilly Media
Purchase Link: Buy Now
Through this book, you’ll learn to explore the opportunities and challenges involved in working with the vast number of datasets made available by the web and learn how to visualize trends in urban crime, using maps and data mashups.
10. Automate This: How Algorithms Came to Rule Our World
Author: Christopher Steiner
Publisher: Portfolio Hardcover
Purchase Link: Buy Now
Through this book, Christopher Steiner tells the story of how algorithms took over—and shows why the “bot revolution” is about to spill into every aspect of our lives, often silently, without our knowledge.
So we’ve looked into the 10 Must Read Books for Data Scientists for both beginner and skilled professionals. Share this post with those people who might be looking for this type of information. For more information on data science, big data, machine learning, and Hadoop you can check out our other articles as well.
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