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12 of 55 people found the following review helpful
Verified Purchase(What's this?)
This review is from: Developing Analytic Talent: Becoming a Data Scientist (Paperback)
First I am not going to spend my time on the subject of "Write a book review, earn $250". My review is without expectation of reward, although I would be honored to have an autographed copy!
I think Dr.Granville has made an outstanding contribution to the field of data science with his web sites and books. I have been eagerly awaiting the release of this book since I first say the table of contents on-line, could order my copy, and was very pleased that Amazon got it to me 2 days before promised. Well done Amazon! And thanks to your founder and president for buying the Washington Post. Second, lets focus these reviews on the book itself. I skim read it and could not put it down. I prepared a tutorial using it for my data science students and our Federal Big Data Working Group Meetup. The organization and content of the book is one of the best I have seen for both those new to data science and for teaching. My only complaint is that the URLs are hard to read and I always long for more data sets and results that can be downloaded to work with to gain hands-on experience. I look forward to Dr. Granville's answers to constructive questions about the book, blogs on additional topics, and to the next book. I think this man deserves more respect and praise for his body of work and this book than he is getting in these early review. Dr. Brand Niemann Director and Senior Data Scientist Semantic Community [...] [...] [...]
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Showing 1-3 of 3 posts in this discussion
Initial post:
Apr 24, 2014, 3:59:47 PM PDT
[Deleted by the author on May 31, 2014, 1:58:24 AM PDT]
Posted on
May 18, 2014, 4:58:00 PM PDT
John S says:
If you really retired as the former "U.S. EPA Data Architect" then I'm scared for the US if such an individual needs more hands-on experience.
In reply to an earlier post on
May 21, 2014, 5:41:05 AM PDT
Christopher Everett says:
Data architects don't do data science, and vice versa.
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