Book Review: Applied Predictive Modeling by Max Kuhn and Kjell Johnson

This is a gem of a book.

From the introduction:

We intend this work to be a practitioner’s guide to the predictive modeling process and a place where one can come to learn about the approach and to gain intuition about the many commonly used and modern, powerful models.

…it was our goal to be as hands-on as possible, enabling the readers to reproduce the results within reasonable precision as well as being able to naturally extend the predictive modeling approach to their own data.

The book is structured into four main sections. First is General Strategies, which provides an introduction and discusses things like pre-processing and tuning. 

The next two sections cover regression and classification, each with chapters on linear and non-linear methods, as well as tree and rule based methods, with one to two chapters on practical issues such as measuring performance. 

The final section covers feature selection, predictor importance and a discussion around model performance. 

Features

There are a few things I really like:

It is not an academic or mathematical treatise; the emphasis is on practice, discussing the issues that commonly arise and how they can be approached. Plenty of references are provided for those wanting to dig deeper.

Every example has its data set and code available so one can work through the examples as presented. In most cases they are real world datasets and there is great discussion of the real world issues that arise, what should be considered and the various tradeoffs that can be made.

Discussion and code are separate. Aside from the excellent content, this is probably what I appreciate the most. Each chapter presents its content, with charts where appropriate, while the actual walk through of the code and raw output is in a separate section of the chapter. 

This makes it much easier to focus on the material being presented. It is always difficult to present source code along with discussion. This is not a book about programming per-se, it is about using existing tools to make intelligent and reasoned decisions about the task at hand. It makes a lot of sense to have the code presented separately.

Also, as far as I have read, each chart is at most only one page away from the text discussing it. This is a small thing but I feel there has been serious consideration about the presentation of the material and it has been done very well. [Update: This is not strictly true but is mostly the case throughout the book]

It is not a book about caret, the package of author Max Kuhn. To be honest I would be pretty happy even if it were about caret, which certainly does get some use in the code, but it is relatively package agnostic. 

Final thoughts

This is a great book, providing both the trees and the forest so to speak. I am unaware of any other book with similar content, and I wish I had something like this when I was first getting interested in machine learning. 

There are books that are very introductory, books that cover the details of the algorithms, and books that provide rigorous coverage of the theory, but these are not really accessible to those without a serious amount of mathematics. There are a few equations presented where appropriate, but it is certainly not the focus of the book.  

There are no real shortcomings, though if there were ever a second edition, coverage of time series methods and deep learning would be welcome. I appreciate they are both book worthy topics by themselves, and the latter is still very much a moving target. 

In summary: Great content, well written and well presented. This book would be my top recommendation to anyone looking to get started or working with predictive modeling. Well worth checking out. 

You can read more reviews on amazon here: Applied Predictive Modeling

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Book Review: The French Revolution: A Very Short Introduction

All work and no play makes Jack a dull boy so I decided to expand my reading circles. I got a copy of The French Revolution: A Very Short Introduction by William Doyle. I am a big fan of the Very Short Introduction series, they are usually a great overview for stuff you would like to know more about but have limited time or a short attention span.

I found the book well written and over all easy to follow, however the prose was slightly heavy in places. The book details the underlying causes, the specific events in chronological order, the aftermath and rise of Napoleon, giving some context to Napoleon's reign, which as an ignorant Australian I had never quite understood.

There were two main things I found interesting. Firstly, the causes were largely economic, France was burdened with crippling debts and its people were suffering due to rising food prices. The leadership of the day was an absolute monarchy, seen to be isolated and out of touch with the travails of day to day common life. The country was experiencing a financial crisis due to protracted wars. This  remained unresolved as the monarchy was beholden to the nobility and clergy, preventing any chance of effective resolution. In practical terms this would have meant tax reform, which the both the nobility and the church were opposed to. I just can't think of a modern parallel.  

The second was its impact on the subsequent 200 years. It gave rise to the concept of the sovereignty of a nation of people, rather than a monarch. It is a reminder that the political structures we have today are still relatively new, and perhaps have not yet reached some optimal maximum. It also showed how the concepts from the Declaration of the Rights of Man and Citizen have found their way into places like the Universal Declaration of Human Rights and formed the basis for many of the liberal democracies we enjoy today.

I really enjoyed reading it, and at 150 pages is not too great a commitment.