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Mining of Massive Datasets

4.41  ·  Rating Details  ·  119 Ratings  ·  9 Reviews
The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for para ...more
Hardcover, 326 pages
Published December 30th 2011 by Cambridge University Press (first published October 27th 2011)
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Ben Haley
Oct 31, 2011 Ben Haley rated it it was amazing
The mining of massive datasets a clear, practical, and studied exploration of how to extract meaning from huge datasets (Terabytes, Exabytes, Petabytes oh my). I recommend the free version.

The book uses practical examples including spam email, google's page rank, and netflix's recommendation service to explore the algorithms necessary to process huge data on infrastructures like map reduce.

The authors have the necessary experience to define the field. Ullman is the powerhouse behind several ven
...more
Natalia Shakhalova
This is a text book for Mining of Massive Datasets course at Stanford. Was very helpful when taking this course at Coursera. It describes different aspects of the domain and the theory behind existing solutions (search engines, networks analysis, recommender systems, online algorithms). It keeps a good balance of strict mathematical theory with all the proofs and references to its practical applications in modern systems. Wide variety of algorithms and ideas for applications in different domains ...more
Yasiru (reviews will soon be removed and linked to blog)
There's an up-to-date free version at http://mmds.org and a full-fledged Stanford MOOC on Coursera. I took the course initially without much reference to the text, but while the lectures were excellent (and the whole course one of the best I've taken on the platform) I wish I'd had more time to go through the book first.
Shane
Aug 06, 2013 Shane rated it really liked it
This is more what I was looking for with the other "Big Data" book I read.
Although, this is quite a bit over my head, and more positioned at college study.

I expect this is something I will reference back to later. I read the "free" pdf version, but I'd like to have a copy of the updated version when it becomes available.
Akash Goel
Nov 18, 2015 Akash Goel rated it really liked it
This book is definitely a great companion of the Coursera MMDS class. But it lacks a few things, such as proper introductions and a natural information flow. Good for quick reference and examples, not too great to study or understand in depth.
Kjn
Dec 20, 2014 Kjn rated it it was amazing
I got a lot from this and that was surprising as I had already read some books here. The nicest part is the Locally Sensitive Hashing.

This is just very good quality. Quite a bit of ideas you can use in your practise.
Victor
Sep 14, 2015 Victor rated it it was amazing
Shelves: a-i, computer-science
I skimmed this book to decide whether to enroll on the Stanford course with the same name, definitely I will enroll on the next available session, very interesting stuff about squeezing information from big data sets
Bryan
Apr 27, 2015 Bryan rated it really liked it
It is a text book. It is a good book for the topic. Not much to say here.
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