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- http://blog.yhat.com/posts/become-a-data-scientist.html |ŷhat Becoming a Data Scientist332 bytes (37 words) - 09:02, 29 January 2017
- |Data Analysis for Novice Programmers. k=to read, programming, python, data analysis, data science, qs318 bytes (39 words) - 13:55, 20 October 2017
- https://www.spectator.co.uk/2016/08/how-more-data-can-make-you-more-wrong/ |How more data can make you more wrong (Replays in slow motion more likely to convict)1 KB (234 words) - 13:27, 16 April 2017
- https://www.inversoft.com/guides/2016-guide-to-user-data-security |2016 Guide to User Data Security - Inversoft431 bytes (48 words) - 09:50, 23 February 2017
- |Map of my personal data infrastructure - beepb00p k= read, qs, data, infrastructure, pkm220 bytes (31 words) - 22:48, 1 June 2021
- |The sad state of personal data and infrastructure - beepb00p196 bytes (30 words) - 23:07, 1 June 2021
- |Generating custom photo-realistic faces using AI – Insight Data390 bytes (47 words) - 12:35, 11 November 2018
- |Part 1, Section 3: Introduction to Using Python for Data Analysis. k=data analysis, python, statistics, qs326 bytes (42 words) - 13:53, 20 October 2017
- |De-Anonymizing Browser History Using Social-Network Data - Schneier on Security343 bytes (44 words) - 17:27, 10 February 2017
- ...https://medium.com/datatau/the-online-courses-you-must-take-to-be-a-better-data-scientist-36a06016c819 |The online courses you must take to be a better Data Scientist - DataTau309 bytes (39 words) - 17:22, 3 July 2020
- https://creators.vice.com/en_us/article/weather-political-machine-learning-data-art |Here's What Happens When You Mix Weather, Political Data, and Machine Learning - Creators317 bytes (37 words) - 10:27, 26 March 2017
- |Hollywood Superstitions vs. Data Science: Investigating for 99PI • Andrew and Zachary Burchill [https://andburch.github.io/qmovies_postmortem/ Hollywood Superstitions vs. Data Science: Post-mortem • Zachary and Andrew Burchill] is the more technical573 bytes (75 words) - 17:18, 7 April 2020
- https://www.kryogenix.org/days/2018/02/20/collecting-user-data-while-protecting-user-privacy/ |as days pass by — Collecting user data while protecting user privacy360 bytes (42 words) - 11:11, 29 April 2018
- https://blog.bigml.com/list-of-public-data-sources-fit-for-machine-learning/ |List of Public Data Sources Fit for Machine Learning - The Official Blog of BigML.com257 bytes (33 words) - 08:01, 7 August 2018
- ...Balance? A Test of the Jack-of-all-Trades Theory Using Military Enlistment Data ...ut'''. In this paper we test this theory using Swedish Military Enlistment data. [...] We find clear support for the Jack-of-all-trades theory, in the sens794 bytes (106 words) - 16:43, 18 September 2017
- https://www.analyticsvidhya.com/blog/2015/07/guide-data-visualization-r/ |Comprehensive Beginners Guide to Learn Data Visualization in R - Learn R397 bytes (43 words) - 13:18, 30 October 2017
Page text matches
- k=data analysis, sleep, irc, quantified self, data visualization, data is beautiful [[Category: Data visualization]]250 bytes (30 words) - 12:29, 21 January 2017
- k=neural networks, ai, images, data mining, data representation, data is beautiful [[Category: Data mining]]568 bytes (83 words) - 17:08, 20 December 2016
- |Part 1, Section 3: Introduction to Using Python for Data Analysis. k=data analysis, python, statistics, qs326 bytes (42 words) - 13:53, 20 October 2017
- https://blog.bigml.com/list-of-public-data-sources-fit-for-machine-learning/ |List of Public Data Sources Fit for Machine Learning - The Official Blog of BigML.com257 bytes (33 words) - 08:01, 7 August 2018
- ...visualization, data is beautiful, data visualization, t-sne, social media, data mining, javascript, grouping, linguistic analysis [[Category: Data visualization]]485 bytes (55 words) - 17:33, 20 December 2016
- k=statistics, math, visualizations, data is beautiful [[Category: Data visualization]]247 bytes (25 words) - 18:23, 17 January 2017
- k=algorithm, potentiallyinteresting, cs, visualization, data, data-mining, data is beautiful, mathematics, math487 bytes (56 words) - 16:58, 20 December 2016
- k=to read, t-sne, dimensionality, ml, data, machine learning, data analysis, data science248 bytes (32 words) - 19:13, 25 January 2019
- |Data Analysis for Novice Programmers. k=to read, programming, python, data analysis, data science, qs318 bytes (39 words) - 13:55, 20 October 2017
- k=analysis, statistics, visualization, data visualization [[Category: Data visualisation]]236 bytes (24 words) - 09:44, 31 July 2017
- |Map of my personal data infrastructure - beepb00p k= read, qs, data, infrastructure, pkm220 bytes (31 words) - 22:48, 1 June 2021
- k=statistics, machine learning, ml, data analysis When a model is too close to the training data.230 bytes (32 words) - 16:41, 22 January 2017
- https://www.kryogenix.org/days/2018/02/20/collecting-user-data-while-protecting-user-privacy/ |as days pass by — Collecting user data while protecting user privacy360 bytes (42 words) - 11:11, 29 April 2018
- k=psychology, happiness, graphs, data, data visualization, to read639 bytes (113 words) - 09:48, 6 May 2019
- k=r, data viz, data visualization, visualisation, visual, statistics, aesthetics, patterns [[Category: Data analysis]]874 bytes (120 words) - 13:18, 30 October 2017
- In fact, if you test 20 hypothesis you don’t need to even bother collecting data to get a p-value of 0.05, the number of hypotheses virtually guarantees it. ...as “outliers”. I used the same technique (linear regression) with the same data set used by the researchers, and I reached the opposite conclusion with a p986 bytes (139 words) - 10:46, 29 May 2017
- http://blog.yhat.com/posts/become-a-data-scientist.html |ŷhat Becoming a Data Scientist332 bytes (37 words) - 09:02, 29 January 2017
- |Hollywood Superstitions vs. Data Science: Investigating for 99PI • Andrew and Zachary Burchill [https://andburch.github.io/qmovies_postmortem/ Hollywood Superstitions vs. Data Science: Post-mortem • Zachary and Andrew Burchill] is the more technical573 bytes (75 words) - 17:18, 7 April 2020
- |GBD Compare : IHME Viz Hub - compare health data in various counties222 bytes (29 words) - 17:17, 20 December 2016
- [[Category: Data representation]]269 bytes (24 words) - 06:47, 16 December 2016