Top 10 Essential Books for the Data Enthusiast
A unique top 10 list of book recommendations, for each of 10 categories this list provides a top paid and top free book recommendation. If you're interested in books on data, this diverse list of top picks should be right up your alley.
Theoretical Machine Learning
Top Paid Recommendation: Pattern Recognition and Machine Learning
The author is an expert, this is evidenced by the excellent insights he gives into the complex math behind the machine learning algorithms. I have worked for quite some time with neural networks and have had coursework in linear algebra, probability and regression analysis, and found some of the stuff in the book quite illuminating.
Top Free Recommendation: Elements of Statistical Learning
The good news is, this is pretty much the most important book you are going to read in the space. It will tie everything together for you in a way that I haven't seen any other book attempt.
Practical Machine Learning
Top Paid Recommendation: Python Machine Learning
This is a fantastic book, even for a relative beginner to machine learning such as myself. The first thing that comes to mind after reading this book is that it was the perfect blend (for me at least) of theory and practice, as well as breadth and depth.
Top Free Recommendation: An Introduction to Statistical Learning with Applications in R
This book provides an introduction to statistical learning methods. It is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences. The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings, and should be a valuable resource for a practicing data scientist.
- Official Website
Deep Learning
As the selection of paid deep learning books is slim at the moment, here are a pair of free selections.
Top Free Recommendation #1: Neural Networks and Deep Learning
Neural Networks and Deep Learning is a free online book. The book will teach you about:
- Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data
- Deep learning, a powerful set of techniques for learning in neural networks
- Official Website
Top Free Recommendation #2: Deep Learning
The in-preparation, likely to-be definitive deep learning book of the near future, written by Ian Goodfellow, Yoshua Bengio, and Aaron Courville. The development version is updated monthly, and will be freely available until publication.
Data Mining
Top Paid Recommendation: Data Mining: Concepts and Techniques, Third Edition
Data Mining is a comprehensive overview of the field, and I think it is best for a graduate class in data mining, or perhaps as a reference book. The book's focus is on technique (i.e., how to analyze data, including preparation), and it addresses all the major topics in the field including data storage and pre-processing. However, the book is really about classification methods, and the 2 chapters on cluster analysis are particularly strong and thorough.
Top Free Recommendation: Mining of Massive Datasets
The book, like the course, is designed at the undergraduate computer science level with no formal prerequisites. To support deeper explorations, most of the chapters are supplemented with further reading references.
- Official Website
SQL
Top Paid Recommendation: Learning SQL, Second Edition
If you're writing any type of database driven code and you think that you don't need to understand SQL, read this book. You do need to understand it, and this book teaches it very well.
Top Free Recommendation: Learn SQL The Hard Way
This book will teach you the 80% of SQL you probably need to use it effectively, and will mix in concepts in data modeling at the same time. If you've been fumbling around building web, desktop, or mobile applications because you don't know SQL, then this book is for you. It is written for people with no prior database, programming, or SQL knowledge, but knowing at least one programming language will help.
- Official Website
Statistics for Data Science
Top Paid Recommendation: Statistics in Plain English, Third Edition
I work as a Data Analyst and deal with statistics on a daily basis. I am expected to know all the models and algorithms. Although statistical software does everything for me, figuring out the numbers the software chews out becomes the tricky part. I majored in Biotechnology and was alien to these statistics for the major part of my life. Long story short, I required a solid foundation guide that would help me get acclimatized to the concepts.
Top Free Recommendation: Think Stats: Probability and Statistics for Programmers, Second Edition
Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets.
- Official Website
Related:
