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Bootstrapping Machine Learning
In an age of overflowing data, Machine Learning and Data Science seem to be all the rage. By analyzing data, computers are able to "learn" and generalize from examples of things happening in the real world. They can make predictions and answer questions such as "How much should I price this product?" and "Which type of document is this?".
Prediction APIs are making Machine Learning accessible to everyone and this book is the first that teaches how to use them. You will learn the possibilities offered by these APIs, how to formulate your own Machine Learning problem, and what are the key concepts to grasp - not how algorithms work, so it doesn't take a university degree to understand.
Prediction APIs are making Machine Learning accessible to everyone and this book is the first that teaches how to use them. You will learn the possibilities offered by these APIs, how to formulate your own Machine Learning problem, and what are the key concepts to grasp - not how algorithms work, so it doesn't take a university degree to understand.
202 pages, Paperback
First published April 1, 2014
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Displaying 1 - 6 of 6 reviews
August 12, 2016
"It doesn't take a university degree to understand"
This simple sentence taken from the book description summarizes my experience exactly.
While I do have a university degree (yay me!) I really didn't feel like wrapping my head around papers and papers filled with technical and specialized language in order to get a feel for the ML field. The book is actually centered on practical usage and it does this very well through an interesting case study which is, for once, a pretty concrete example.
The book definitely won't help you fine-tune your custom made ML algorithms but it will definitely show you why you're most likely wasting a lot of time doing this while you could actually leverage the power of Prediction APIs.
This simple sentence taken from the book description summarizes my experience exactly.
While I do have a university degree (yay me!) I really didn't feel like wrapping my head around papers and papers filled with technical and specialized language in order to get a feel for the ML field. The book is actually centered on practical usage and it does this very well through an interesting case study which is, for once, a pretty concrete example.
The book definitely won't help you fine-tune your custom made ML algorithms but it will definitely show you why you're most likely wasting a lot of time doing this while you could actually leverage the power of Prediction APIs.
June 17, 2014
I recommend this book to anyone interested in using prediction APIs. It provides a very interesting approach to machine learning by focusing on easy-to-use cloud based services. If you do not have any prior experience in the field, this is not a problem, the concepts are well explained and the author use a step by step approach with the use of concrete examples.
October 28, 2019
As an introduction to Machine Learning, is as good as they come. Clear, precise and straightforward. Worth reading.
June 17, 2014
I wrote the book...
October 5, 2015
Consider this essential reading. Very clear, straightforward.
For once, a Computer Science book that doesn't measure its value in 1000s of pages!
For once, a Computer Science book that doesn't measure its value in 1000s of pages!
November 18, 2015
Louis does a great job of getting the fundamentals of machine learning into understandable chunks that can then be applied to real-world use cases.
Displaying 1 - 6 of 6 reviews