File Size: 15924 KB
Print Length: 318 pages
Publisher: O'Reilly Media; 1 edition (May 10, 2017)
Publication Date: May 10, 2017
I actually dislike that the writers make a number regarding categorical statements of the particular form " Data Scientists do this" or " Data Scientists don't require that". I disagree with many of these statements and I think they have used a definition of " information science" that is narrower than the prevailing consensus inside the industry.
This publication has some errors (see, for example, the misunderstandings matrix on page 196) but overall the accuracy is above average family member to recent norms.
As other reviewers have mentioned, the author's github database for the book happens to be empty. If that's essential to you, check it under " andrewgbruce" upon github and make sure it's been updated before you purchase the book., There's always that one individual who is unsatisfied, but it sure as hell isn't me, because I knew what this guide was going to be able to be like the moment I could see how many pages it was going to possess & how the earlier release version looked. I actually still preordered a hard copy (for sharing) as well as an electronic digital copy (for carrying), because I knew this was kind of what type of book I was looking for & then a few.
The concepts are not astronomically explained, but with sufficient depth that I could also individually explain to be able to people what they usually are. What really stands out there for me to date is after each or so concept, there is a area labeled as further reading (well, inside the digital copy) that will is usually at the particular end of the publication altogether & I identified myself realizing I possess a lot of those books so the writers really know where to be able to look & guide those who wanted more detail.
Yeah yeah yeah, the particular codes are missing (as of mid-June 2017) but if you really understood / understand which packages to make use of, you wouldn't need the particular code. The very first half regarding the book are two three liners of code concepts anyways; it's the particular explanations that matter the particular most. The second half regarding the book is the particular good part, which isolates a white hat statistician from your grey hat information scientist, which is precisely what I wanted in a < 300 page publication.
Thanks for keeping me waiting since November though, thought it would never come! The O`Reilly publications always keep me inside awe at how they always know what matter I wish to have a quick book (probably data collecting on me: P) as well as simultaneously leave me inside suspense because I never notice I am preordering the books! Sigh. The only request is to be able to be able to preorder the particular Kindle editions rather than the physical editions; our data science book cubby is starting to overwhelm my statistics cubby (OFCOURSE NOT FOR LONG MASTERS PROGRAM ~)., Information seems obviously written and relevant. Simply no connect to datasets makes the particular " practical" code part of the book useless. Will happily update our review when the datasets are released.
Ok the datasets are up. There is a short R script to run to down load the data, it will require some small alterations to get it functioning correctly.
You need to be able to produce a folder named " data".
and I changed the second line inside the script from:
PSDS_PATH < : file. path('~', 'statistics-for-data-scientists')
PSDS_PATH < - document. path('. ')
This will download the data in to a folder named " data" in whatever directory site you run the script. The script runs with no real feedback and several of the data units are large, so merely be patient. Once these types of were downloaded the illustrations in the book run great., Excellent introductory text message for a comprehensive overview regarding statistics! The github database augments the information very well and provides added value for the statistical topics covered in the publication. Both of the Bruce brothers are statistical gurus and this fact is evident in the writing, which is both informative and witty. Peter is the president of Statistics. com and is well-versed inside providing statistical instruction to be able to students of everyone in addition to levels. He is also a proponent of resampling in addition to one in the developers regarding the excellent Resampling Numbers software package for Excel.
It really is true that the particular textbook would not provide in-depth coverage for all those topics, nevertheless I do not think that was the intent in the writers. However, the text WILL provide an excellent launch to topics relevant to be able to students and data researchers. After reading the text in addition to working through the illustrations, you will be prepared to further your understanding inside whichever topic you require regarding you data analysis job.
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