Timeline for What open-source books (or other materials) provide a relatively thorough overview of data science? [closed]
Current License: CC BY-SA 3.0
13 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| S May 16, 2014 at 13:45 | history | suggested | IgorS |
Added relevant tags
|
|
| May 15, 2014 at 21:08 | comment | added | blunders | @statsRus: Try posting a question like that to SO, and it'll be closed; these questions exists because they have historical significance, but they are not considered good, on-topic questions for Stack Exchange sites, so please do not use them as evidence that you can ask similar questions here. | |
| May 14, 2014 at 8:40 | history | closed |
demongolem senshin Bill the Lizard Sean Owen Konstantin V. Salikhov |
Not suitable for this site | |
| May 14, 2014 at 7:55 | answer | added | Konstantin V. Salikhov | timeline score: 6 | |
| May 14, 2014 at 6:12 | review | Suggested edits | |||
| S May 16, 2014 at 13:45 | |||||
| May 14, 2014 at 6:06 | answer | added | IgorS | timeline score: 8 | |
| May 14, 2014 at 2:49 | vote | accept | statsRus | ||
| May 14, 2014 at 2:35 | comment | added | statsRus | Fair enough regarding what constitutes a "valid" question, although on other SE sites this question would not be immediately closed as you've stated: e.g., 2495 votes, 1440 votes, 168 votes, and so on. There's great interest for these kinds of questions, even if this isn't deemed the right place. | |
| May 14, 2014 at 1:34 | review | Close votes | |||
| May 14, 2014 at 8:40 | |||||
| May 14, 2014 at 1:16 | comment | added | demongolem | This question appears to be off-topic because it is asks for a favorite resource. On other SE sites, this would immediately be closed. Since this is a new site, we still have to decide if this is a valid question here | |
| May 14, 2014 at 0:53 | answer | added | Nick Peterson | timeline score: 13 | |
| May 14, 2014 at 0:38 | comment | added | Ansari | List questions are usually not suited for Stack Exchange websites since there isn't an "objective" answer or a way to measure the usefulness of an answer. Having said that, one of my recommendations would be MacKay's "Information Theory, Inference, and Learning Algorithms." | |
| May 14, 2014 at 0:11 | history | asked | statsRus | CC BY-SA 3.0 |