File Size: 13978 KB
Print Length: 147 pages
Publication Date: February 3, 2017
This read is helpful to break down ML concepts for business and industry...
Thanks again.,Excellent intro to ML. Goes into enough plain English description of relevant techniques to help you understand the mathematics which you read about in more technical books.,Very good introduction to the algorithms. Easy to understand and choose the correct one. Loved random forest, a collection of trees,This is an excellent book both in depth and breadth of
the topics covered. It gives descriptions, analyses, and insights
about the most popular algorithms on various topics, and it covers
many more areas than most books. The book is well integrated across
the broad diversity of topics that are covered, and connections between
methods and topics are pointed out throughout the book. For most of the
important topics, a lot of detail is provided in terms of algorithm description
and pseudo-code. In some cases, interesting analyses are also provided.
For instance, in the case of frequent pattern mining algorithms,
not only are more algorithms discussed
than most of the other books, but a discussion of multiple choices
of data structures for the same algorithm is provided,
along with their relative trade-offs. The relationships among various
algorithms are also discussed. I have seen quite a
few textbooks on data mining, and I have not seen anything close to this
level of detail in any of the other books. Overall, my impression is
that the authors have done an excellent job of calibrating detail level
to topic importance. Therefore, it can serve both as a textbook and
as a reference book. On the other hand, this is certainly
not an implementation or programming-centric book. The book is good at
teaching principles and concepts.,Very, very informative.,The book is really what it's described as: data science for the layman, without any math! I'm pleasantly surprised at how accessible the concepts in the book are, as the authors have done a great job in condensing the wealth of information into very easily understood ideas.
The book is well-written and edited, and the illustrations look amazing and work well together with the text. The examples chosen made it easier for me to understand the concepts.
As someone without any data science background, this book was definitely a great read for me! Even for someone who has experience in data science, I feel that after reading the book, it'll be easier for you to share the subject with your friends through the simplified concepts and relatable examples. Would definitely recommend the book!,Fantastic primer on data analytics. Highly recommend to anyone interested in learning more about this fascinating subject area. Introduces the major methods in simple terms.,I know nuts about data science but this book is surprisingly easy to understand! I particularly love the examples that accompany each chapter. The examples relate to everyday life and effectively narrate the concepts in each chapter. I would recommend this to anyone who wants to have a quick but yet in depth overview of what Data Science is about.
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