Recently Packt Publishing released the second edition of Mastering Azure Machine Learning by Christoph Körner and Marcel Alsdorf and, given my love for machine learning on Azure, I had to read it. After a month of off and on reading, I’ve finished it and I have to say that I’m very impressed.
Disclaimer: Packt Publishing provided a copy of this book at no cost for reviewing purposes.
It’s a longer book at 574 pages before the final indexes, and the contents of each page are dense, requiring a lot of focus and energy to read it, but bottom line: Mastering Azure Machine Learning is an amazing book for those wanting to dive deeper across the full spectrum of topics related to machine learning on Azure.
This is not a book on passing a certification, though its contents would certainly be extremely helpful for those studying for the Azure Data Scientist exam (DP-100). This is a book on gaining significant depth and comfort across the breadth of data science offerings on Azure in Azure Machine Learning Studio and via the Python SDK. The book even goes beyond these bounds, however, to explore the different algorithms in data science, Azure Cognitive Services, data visualization, MLOps, and more.
This is not the book that I would recommend as a first learning resource on data science or even necessarily on Azure Machine Learning. If you’re looking to get a general overview of AI or machine learning on Azure, there are other resources out there for that. Additionally, there are other resources out there dedicated towards individual certifications such as the DP-100 Azure Data Scientist materials or the AI-900 Azure AI Fundamentals materials.
Instead, this is a book to read if you’re working with machine learning on Azure and want to get really, really good at it. If you want a guided tour of the ins and outs of Azure Machine Learning, what you might use when, what capabilities are available, and how to specifically implement things to meet you and your organization’s needs, this is your book. Each chapter is a wealth of information about a very specialized topic.
Many chapters were beyond what I had explored before reading, but for the many that overlapped my knowledge, I can attest to the quality of the material and even learned some new things about processes I’d worked with a lot.
This is not a book for everyone but if you’re familiar with Azure Machine Learning and want to dig deeper, this book is going to help make you amazing.