Machine Learning with Spark

As a Software Developer with a basic understanding of ML, this book is perfect as it walked thru the most popular flavours of today's ML challenges with apache spark powered solutions.Code examples are clean, effective and easy to understand and test yourself

Perfect book for someone who is just starting his adventure with Spark and Machine Learning. The author has very didactic approach that guides the reader step by step from understanding first the basics, installing the environment, implementing and training models, evaluating, etc. I strongly recommend this book.

It's a pity that this worthwhile book is held back by thoughtless negative reviews. I have now seen ten or so Spark books - see my other reviews - and "Machine Learning with Spark" gets into my top 3, alongside "Spark in Action" by Bonaci and Zecevic, and "Spark for Data Science" by Duvvuri and Singhal. "Spark in Action" is a quality book, but a little on the heavy/plodding side. "Machine Learning with Spark" is a lighter introduction, which - unlike 99% of Packt-published books, mostly low-value-added copycats - can manage explanation of concepts, and is generally well written. I do think that at present "Machine Learning with Spark" is the best starter book for a Spark beginner.

Too much emphasis on scala not enough on python. The examples are half-baked code and you always have to fill in the gaps in between lines. Why can't they just give you example codes to execute? The author also wasted their time and effort explain the background behind each model, like k-means. The results are half-baked and probably impossible to follow unless you already knew that the models, so it was all a waste of time. I am an experienced data scientist and frankly was not able to learn scale or spark from the book.

This book is a nice introduction to using the Apache Spark framework. It assumes no prior knowledge of either Hadoop, Spark or machine learning itself (although the latter is covered at quite a rapid pace in places so some background would likely be helpful!). The code examples are presented in Python and (mainly) Scala, with examples that are reasonably well-described.The overall tone of the book is clear and the chapters progress in a logical order, with a fairly rapid journey through the main machine learning techniques from a Spark perspective. Later chapters were particularly interesting, covering text mining and more complex methods (e.g. feature hashing).Some of the example data sets feel a little 'tired' (movie ratings data yet again - or perhaps I've just read too many machine learning books), but otherwise this is a good book and comes recommended.

This book gives a great introduction to using the Apache Spark framework, a goto for anyone who wishes to learn how to use Apache Spark framework. It assumes no prior knowledge of either Hadoop or Spark. The code examples are presented in Python and Scala are well-described.The overall the book is clearly structured and the chapters progress in a logical order, with a fairly rapid introduction to machine learning techniques from a Spark perspective.I definitely do recommend this book for beginners.

This is not a great book.

Did not find as useful as ML in R by Bret Lantz