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Ехал Data через Data

Logo of telegram channel dataoverdata — Ехал Data через Data Е
Logo of telegram channel dataoverdata — Ехал Data через Data
Channel address: @dataoverdata
Categories: Uncategorized
Language: English
Subscribers: 29
Description from channel

Всякое про #BigData, #DataAnalysis / #DataScience, #ML

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The latest Messages

2018-10-31 11:22:52 https://gist.github.com/versipellis/eb15f8612be76d49922e3e2490e50612 #podcasts #ml
159 viewsedited  08:22
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2018-08-25 14:23:06 Интересное про пин-коды карт :)

There are 10,000 possible combinations that the digits 0-9 can be arranged to form a 4-digit pin code. Out of these ten thousand codes, which is the least commonly used?

Which of these pin codes is the least predictable?

Which of these pin codes is the most predictable?

If you were given the task of trying to crack a random credit card by repeatedly trying PIN codes, what order should you try guessing to maximize your chances of selecting the correct number in the shortest time?

http://www.datagenetics.com/blog/september32012/
215 views11:23
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2018-08-25 14:20:48 We've designed a distributed system for sharing enormous datasets - for researchers, by researchers. The result is a scalable, secure, and fault-tolerant repository for data, with blazing fast download speeds

http://academictorrents.com/
154 views11:20
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2018-08-25 00:28:12 This visualization shows books often bought with the Designing Data-Intensive Applications, written by Martin Kleppmann.

https://anvaka.github.io/greview/ddia/1/
122 views21:28
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2018-08-25 00:27:41 Воскрешаю канал :)
109 views21:27
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2018-03-24 16:13:44
172 views13:13
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2018-03-23 03:08:23 Ещё Ларри шутил на эту тему называя свой язык Perl

«Poor data quality is a familiar problem for those who analyze data for a living. A recent survey found that 60% of data scientists devote the majority of their time to cleaning and organizing data, as shown in Figure 1.
...
When people predict that AI will make human workers obsolete anytime in the near future, they are ignoring the data quality problem. AI and machine learning may be able to replace those 9% of data scientists who are mining data for patterns, but it will still need the 80% working on collecting, cleaning and organizing data.»

https://seekingalpha.com/article/4158018-ai-big-data-problem
170 viewsedited  00:08
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2018-02-12 15:38:30 Joel Grus – Fizz Buzz in Tensorflow
http://joelgrus.com/2016/05/23/fizz-buzz-in-tensorflow/ #fun #ml
116 viewsedited  12:38
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2018-02-08 10:37:21 Different continents, different data science - O'Reilly Media
https://medium.com/@acroll/different-continents-different-data-science-703f5114366 #thoughts
124 viewsedited  07:37
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2018-02-08 10:28:05 https://gdpr-info.eu #law #privacy #europe
108 viewsedited  07:28
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