For those interested in learning about big data, Machine Learning, data analytics, and more of the like, data science books can make all the difference.
What is big data? What are the implications of artificial intelligence in current and future computing, and for that matter, in society as a whole? How does one sort through all of the information?
If you seek to understand some of these hot topics, there are likely some data science books out there that can really help make it easier. From world-renowned experts like Ng, Provost, Gulli, McDowell, and others, these data science books are essentially passports into the minds of the foremost experts on these very subjects. With all this said, which data science books are right for your particular interests and learning needs? Here’s a brief rundown of 30 of the top picks in this uniquely educational area of tech and data books today.
#1 – Data Structures and Algorithms in Java
Algorithms and data structure are becoming more standard in today’s tech world than at any time ever before in history. In this great explanation of it all, expert and author Robert Lafore provides a veritable workshop of written explanations, reader-usable samples, examples, and more. Additionally, this second edition version adds plenty of user-friendliness to the equation beyond the original series entries.
#2 – Data Science For Dummies
Whether you are already quite experienced and looking for warm-up material, or you are just starting out in data science, Data Science For Dummies is a fabulous resource to have at hand. In this For Dummies series member, author Lillian Pierson breaks down all of the fundamentals of data science. Prepare to understand big data, data engineering, IT fundamentals, and more in this educational classic.
#3 – Keeping Up with the Quants: Your Guide to Understanding and Using Analytics
Thomas H. Davenport
Marketing pros, data and finance workers, managers and many others can really benefit from this fantastically helpful guide to analytics by author Thomas H Davenport. In a world full of data, understanding its interpretation is quite the valuable skill. Learn the ins and outs with relative ease in one stop right here.
#4 – Machine Learning Yearning
In the emerging and often controversial world of artificial intelligence, there can be so much to ponder, on the science side as well as the layman’s side. This piece by noted expert Andrew Ng explores many of the obvious and not-so-obvious concepts to consider along this impassioned subject. For those wanting to further understand the overall potential of AI, this book is a great choice.
#5 – Blockchain Technology And Data Analytics
Isaac D. Cody
Today’s new and rapidly growing digital currencies and economies are based almost solely on technological method. Blockchain Technology And Data Analytics provides the reader with a straight-to-the-chase explanation as to how it all works. Learn about transacting, security layers, blockchain structure, and more in this all-inclusive rundown.
#6 – Data Smart: Using Data Science to Transform Information into Insight
John W. Foreman
Data Smart: Using Data Science to Transform Information into Insight offers the reader a great dose of a number of crucial concepts in data use today. As a result, readers of this great will learn about data mining, analytics, forecasting methods and more – all in the name of better utilizing the data that is out there just waiting to be used. You certainly don’t have to be an IT wizard to benefit from this insightful guide.
#7 – Grokking Algorithms: An illustrated guide for programmers and other curious people
No matter who you are, if algorithms are of interest to you, then this book is an absolute must. As it turns out, these coded communication sets can be used in computers as well as in the real-world environment. They can also be created and mastered by virtually anyone. This is the fundamental-loaded, how-to guide for doing exactly that.
#8 – Data Analytics Made Accessible
Dr. Anil Maheshwari is a highly respected professor and expert in data and various disciplines within information technology. Data Analytics Made Accessible is Meheshwari’s extremely helpful guide to data analytics and making its uses accessible in just about any environment. Thorough explanations, easily understood example segments, and more await the learner here.
#9 – Data Analytics Guide: For Beginners Introduction
Everything you need to know to get started working with data analytics is likely contained within the pages of this great by author William Sullivan. Time, resources, and data all intersect, and this is the explanation of why and how. Learn about web scrapping, data mining, regression analysis, business intelligence, and more.
#10 – The Data Science Handbook
Some of the best insights in data science don’t necessarily need to come from guidebooks and written, traditional styles of explanation. This hit among data science books proves that by offering a great learning experience via interviews with leading minds in the industry. Prepare to see things from their perspectives – greats like Hilary Mason, Kevin Novak, Bradley Voytek, and many others.
#11 – BITCOIN: Bitcoin Investing, Trading, And Mining – The Complete Guide To Understanding Bitcoin
George Icahn, the famed business magnate and investor provides us with this telling guide all about the cryptocurrency, Bitcoin. Within its pages, the reader will learn all about blockchain processes as well as the thorough fundamentals of Bitcoin itself. In addition, investment techniques are also covered for those interested in taking their Bitcoin exploits one step further.
#12 – Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
Foster Provost and Tom Fawcett
With a specific angle in business, Foster Provost and Tom Fawcett have created a masterful business-bible all about data and its analysis. While machines can do much of the work, the human mind is still an important input for sorting through it all. This is how businesses can really take advantage of the vast world of data and the human element.
#13 – Streaming, Sharing, Stealing: Big Data and the Future of Entertainment
Michael D. Smith, Rahul Telang
The crossroads of the entertainment industry and big data is a rather fascinating one, full of learning moments for those aware of the story. This is that story, beautifully laid out by authors Michael D. Smith and Rahul Telang. What does the past tell us about tomorrow? Read this one to discover the truth.
#14 – R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Hadley Wickham and Garrett Grolemund
For those wishing to become proficient in R and RSTudio, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data is a great choice in learning materials. Understand the Tidyverse and R packages for all different applications. One could best describe this one as intuitive and clear coverage of an otherwise tough set of concepts for many.
#15 – Doing Data Science: Straight Talk from the Frontline
Cathy O’Neil and Rachel Schutt
Doing Data Science: Straight Talk from the Frontline is actually based on the introductory class for data science at Columbia University. Essentially, this is a collection of insights and lectures getting the reader up to speed with data use in the business world today. Learn from Google, Microsoft, Ebay, and other engineering experts on the forefront.
#16 – Show Me the Numbers: Designing Tables and Graphs to Enlighten
If you need to sharpen your skills in visual math tools such as graphs and charts, Show Me the Numbers: Designing Tables and Graphs to Enlighten is an outstanding ode to just this concept. What makes some graphics better than others, and how does one go about crafting the very best visuals for the situation at hand? Author Stephen Few makes anyone an expert.
#17 – Cracking the Coding Interview: 189 Programming Questions and Solutions
Gayle Laakmann McDowell
As a seasoned software engineer, author Gayle Laakmann McDowell knows plenty about coding, algorithms, software design, and more. This is her brilliantly helpful guide to this whole sector of know-how. Knowing the material, presenting as the best candidate at the interview, and other, valuable trade secrets are all shared here.
#18 – Numsense! Data Science for the Layman: No Math Added
Annalyn Ng and Kenneth Soo
For those wanting the absolute most dumbed-down, basic introduction on how algorithms work, Numsense! Data Science for the Layman: No Math Added is a perfect selection. When all other explanations seem futile, the way it’s covered in this piece makes the subject impossible not to understand. Advanced users may not need this one so much, but for beginners, this is a virtual bible.
#19 – Cracking the Tech Career: Insider Advice on Landing a Job at Google, Microsoft, Apple, or any Top Tech Company
Gayle Laakmann McDowell
Hitting our list of the best data science books again is author Gayle Laakmann McDowell, this time with her hit piece on getting jobs at some of the most prestigious tech companies today. What would an insider advise of the job candidate here? It’s all disclosed in this tell-all guide.
#20 – Applied Predictive Modeling: An Overview of Applied Predictive Modeling
Predictive modeling is a somewhat complex math approach to applying the use of statistics in order to perform accurate date forecasting. In this piece, Steven Taylor breaks this otherwise complex subject into easily digested subtexts. Get to know the most common predictive modeling approaches and with which situations each is best utilized.
#21 – Making Money out of Data: The Art and Science of Analytics
As its title suggests, Making Money out of Data: The art and science of Analytics is one of those data science books uniquely aimed at helping one to really make the most of something that is readily available all around us – data. This is a guide to the expert tricks and way of seeing things that truly can make profitability a possibility in even the most unlikely of places. Learn to make money from data.
#22 – The End of Error: Unum Computing
John L. Gustafson
Unum is a relatively new term which means “universal number.” Unum is also poised to be the biggest breakthrough of our times in changing the way computers actually do their computing. Written by the creator of Gustafson’s Law and world-renowned expert John L. Gustafson, this selection takes the reader on a fascinating journey into the brains of computing, today and tomorrow.
#23 – Life 3.0: Being Human in the Age of Artificial Intelligence
How will society be affected as artificial intelligence expands its role in all that we do? This is expert Max Tegmark’s unadulterated take on what is likely to become our revolutionary new world. Tegmark himself is a notable MIT professor specializing in AI research and application work.
#24 – Hyper: Changing the way you think about, plan, and execute business intelligence for real results, real fast!
Gregory P. Steffine
Hyper: Changing the way you think about, plan, and execute business intelligence for real results, real fast! is a shining compass in the often complex world of business intelligence and decision-making today. Author Gregory P. Steffine takes the reader on an intuitive and smooth, yet information-filled journey through the world of business intelligence. Learn what counts, what doesn’t, and how to utilize it all.
#25 – Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners
Machine Learning is a fairly new concept involving basic levels of artificial intelligence able to be applied and used by nearly any user and on nearly any computer. This is the comprehensive introduction to that very topic. Having read this one, the reader will find themselves quite adept at the basics of this new and hybrid form of AI.
#26 – Big Data: A Beginner’s Guide To Using Data Science For Business
Eliot P. Reznor
This is another great among data science books which are meant to give a rundown of the fundamentals of data science and its use in business in particular. For use in sales, marketing, inventory management, or even records management, there’s an application here for virtually every business and business function. As a “Beginner’s Guide,” easy implementation is a closely-followed and very welcoming theme here.
#27 – Painting By Numbers: How to sharpen your BS detector and smoke out the “experts”
Painting By Numbers: How to sharpen your BS detector and smoke out the “experts” is one of those more memorable data science books due to its enjoyable approach and applicability. So much data and supposed fact is thrown around today. Do you know which is newsworthy and which should be ignored altogether? Refine your senses with this colorful eye-opener by author and expert Jason Makansi.
#28 – The Art of Data Science
Author and expert Roger Peng provides us with another great in data science books with The Art of Data Science. In this trusted guide, Peng teaches the art of dissemination and use. To use data to maximum benefit, a company must be able to disseminate practicality from valueless data and then go on to efficiently apply it in some way. This is a fantastic guide on the subject.
#29 – Data Science from Scratch: First Principles with Python
While many tools and a starting foundation from which to build codes and algorithms can be extremely helpful, this guide by Joel Grus proves the beauty in coding from scratch. Learn how to work without tool kits, applications, frameworks and assistive modules. The how-it-works of math and computer science collide spectacularly in this highly educational piece on from-scratch coding.
#30 – A Collection of Advanced Data Science and Machine Learning Interview Questions Solved in Python and Spark (II)
Dr Antonio Gulli
Machine learning is set to transform much of the computing world. Big data, however, turns out to play a notable role in this assured evolution in hybridized AI techniques. This guide by expert Antonio Gulli takes aim at this intersection of high-value computing concepts as well as Python and Spark platform interview questions and approaches. Dr Gulli himself is a famed expert and writer of a diverse variety of data science books today.
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