Applied Predictive Modeling – Book Review

Screen Shot 2015-06-30 at 1.58.06 PM“Data Science” is the most exciting research and professional fields these days. It is creating a lot of buzz, both within the academy as well as in the business world. Detractors like to point out that most of the topics and techniques used by people who call themselves Data Scientists have been around for decades if not longer. However, has often been the case that a combination of topics and methodologies becomes important and concrete enough that a truly new subfield emerges.

Predictive Modeling is a particularly exciting subfield of Data Science. Thanks to the few recent high profile news grabbing success stories (the 2012 US presidential election, the Netflix prize, etc.) it has attracted a lot of attention and prominence. Thanks to the increased use and availability of data in all walks of life we are increasingly able to make reliable predictions and estimates regarding topics and issues that affect us in very substantive ways. This ability may sometimes seem almost magical, but behind it lay some very accessible ideas and techniques. “Applied Predictive Modeling” aims to expose many of these techniques in a very readable and self-contained book.

This is a very applied and hands-on book. It guides the reader through many examples that serve to illustrate main points, and it raises possible issues and considerations that are oftentimes overlooked or not sufficiently reflected upon. For instance, the way we model as simple of a data as a calendar date can have a significant impact on the kind of analysis and predictive model we choose. This is the kind of information that is often not discussed in other modeling books and can sometimes take years of practical experience before its impact is fully appreciated.

The book has a fairly low access bar, but it is definitely not intended for a complete novice. It assumes a fairly decent background in statistics, R language, and at least a passing understanding of machine learning. Many of these techniques are covered in this book, but mainly as summaries and refreshers. Each one of them could use up a book of its own, ore even a whole collection of books.

One of the best features of this book is that the authors understand that predictive modeling is not just a bunch of statistical and computational techniques. Understanding the data, how to obtain it, manipulate it, and format it, are some of the most crucial steps for predictive modeling (and other data-driven fields), and are often overlooked and not sufficiently explained in many other books and papers that I have come across. The same can be said about the model selection – the choice of a model and its predictive power will crucially depend on the kind of phenomena that we are predicting, as well as on what exactly are we trying to predict. This book does an excellent job in guiding the reader along these paths and installing the necessary intuitions required for successful predictive modeling. Here too, like with most things in life, there is no substitute for years of experience working with actual real world problems, but going through this book will ensure that you don’t have to stumble too much with your first steps.

Highly recommended.

**** Book provided for review purposes. ****


Bojan Tunguz

Bojan Tunguz was born in Bosnia and Herzegovina, which he and his family fled during the civil war for the neighboring Croatia. Over the past two decades he has studied, lived and worked in the United States. He is a theoretical physicist with degrees from Stanford and University of Illinois. Tunguz has taught physics at several prominent liberal arts colleges and has been writing about physics, science and technology for more than a decade. He also has a wide spectrum of interests, and reads and writes about current events, society, culture, religion and politics. Over the years he has reviewed many of the books that he has read, and posted his reviews on various online outlets. In 2011 he had become a top 10 reviewer on, where he continues to be very active. Aside from reading and writing, Tunguz enjoys traveling, digital photography, hiking, and fitness. He resides with his wife in Indiana. You can follow my review updates on the following pages as well: Facebook: Twitter: Google+:

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