The third book that I finished this vacation were Machine Learning Hands-On for Developers and Technical Professionals by Jason Bell published by Wiley. The author is a person that have worked extensively with analysis of point-of-sales data since 2002 and as a developer for the past 25 years. The aim of the book is to show the reader how machine learning techniques can be applied to data to solve business problems through hands-on labs.
The table of contents looks like this:
Chapter 1: What is Machine Learning?
Chapter 2: Planning for Machine Learning
Chapter 3: Working with Decision Trees
Chapter 4: Bayesian Networks
Chapter 5: Artificial Neural Networks
Chapter 6: Association Rules Learning
Chapter 7: Support Vector Machines
Chapter 8: Clustering
Chapter 9: Machine Learning in Real Time with Spring XD
Chapter 10: Machine Learning as a Batch Process
Chapter 11: Apache Spark
Chapter 12: Machine Learning with R
I read the book on my Kindle and I did not do the labs but because of illustrations and code listings I had no problems following along.
What I thought of the book
I found the book an interesting read I liked how the author laid out the subjects. He gave a lot of examples and also went through some of the math behind the algorithms. However I got the feeling that he had not made up his mind on what the book should be. From chapter 9 and onward the book was much more a Hadoop/Spark/Spring XD book than anything else and the only examples used was variations on word count with some twitter analytics thrown in. In his introduction the author talks about that machine learning are systems that learn and improve with experience yet the text analysis that he shows is simple word matches instead of real NLP implementations.
Who I think should read it
Developers that want to get an introduction to machine learning and the tools used. Most of the examples are in Java so it is good if the reader can follow along with code in that language.