Book review: Predictive Analytics with Microsoft Azure Machine Learning
Right now I am on an extended holiday and I have had some time to tick of some books from my reading list. I thought that I would take some time to write a couple of short reviews on the books that I have read.
The first one is Predictive Analytics with Microsoft Azure Machine Learning: Build and Deploy Actionable Solutions in Minutes by Roger Barga, Valentine Fontama and Wee Hyong Tok released on Apress.
I have read the Kindle version of the book and found it to really work well in that format. The book consist of 8 chapters that tries to teach how to apply Azure Machine Learning to solve various business problems.
The table of contents look like this:
Chapter 1: Introduction to Data Science
Chapter 2: Introducing Microsoft Azure Machine Learning
Chapter 3: Integration with R
Chapter 4: Introduction to Statistical and Machine Learning Algorithms
Chapter 5: Building Customer Propensity Models
Chapter 6: Building Churn Models
Chapter 7: Customer Segmentation Models
Chapter 8: Building Predictive Maintenance Models
The first section (chapter 1-3) serves as an introduction to the area and the service and its features. Section 2 (chapter 4) contains information on the algorithms applied in the rest of the book. The last section, section 3 (chapter 5-8) shows how you can apply algorithms to solve real problems.
What I thought of the book
I do not claim to be a data scientist or an expert in machine learning but I have been using Azure Machine Learning in real life. Still I found the book valuable, I learnt some new techniques and got some valuable background information. What I really found valuable was the notes and references to other books and papers especially when they did not come from Wikipedia. What could have been covered to greater extent would have been data preparation. How do you prepare a dataset for let's say churn analysis? In the book the examples often started with a sample set that had been pre-prepared earlier.
Who I think should read it
Someone with a background in data science or BI who wants to learn Azure ML but wants something more than the tutorials available in the help pages for Azure ML.