Book Review: Microsoft Azure Machine Learning by @sumitmund
Microsoft Azure Machine Learning by Sumit Mund is a good beginner level book that made Azure ML a little less daunting for me. I'll keep going back to it as I continue to learn & experiment more with Azure ML, the amazing predictive analysis tool that makes it easy for developers to leverage complex Machine Learning algorithms all within the web browser.
Having quickly read through the book to familiarize myself with Machine Learning jargon & tried some of the samples, I've realized it'll take me more reading and practice to achieve proficiency. This 200+ paged book whets your learning appetite by covering a breadth of topics with just enough information to get you started but not too much to make it too intimidating for newbies.
It helps that the author makes practical tips & recommendations rather than just pontificating. Sample -
Outliers are data points that are distinctly separate from the rest of the data... In many cases, it is a good idea to clip or remove the outliers.
As with anything related to the Cloud, most info has a limited shelf-life - a serious threat to books & documentation. As Azure ML Studio continues to evolve, some things have changed since the book was written. Therefore you'll find that some Modules described in the book have new names and it is an exercise for the reader to identify the differences.
A little more effort could have been spent in presenting the content better. While the author provides background context for most keywords before introducing them, there were a few instances where the author drops keywords without adequate explanation like in the case of "ports".
Despite the minor blemishes, this book is engaging and well-structured. It helped me appreciate the understated power of Azure ML.
Having quickly read through the book to familiarize myself with Machine Learning jargon & tried some of the samples, I've realized it'll take me more reading and practice to achieve proficiency. This 200+ paged book whets your learning appetite by covering a breadth of topics with just enough information to get you started but not too much to make it too intimidating for newbies.
It helps that the author makes practical tips & recommendations rather than just pontificating. Sample -
Outliers are data points that are distinctly separate from the rest of the data... In many cases, it is a good idea to clip or remove the outliers.
As with anything related to the Cloud, most info has a limited shelf-life - a serious threat to books & documentation. As Azure ML Studio continues to evolve, some things have changed since the book was written. Therefore you'll find that some Modules described in the book have new names and it is an exercise for the reader to identify the differences.
A little more effort could have been spent in presenting the content better. While the author provides background context for most keywords before introducing them, there were a few instances where the author drops keywords without adequate explanation like in the case of "ports".
Despite the minor blemishes, this book is engaging and well-structured. It helped me appreciate the understated power of Azure ML.
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