Machine learnings 2015 top influencers
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Transcript of Machine learnings 2015 top influencers
By Tom Howells, Staff Writer, Fraud & Technology Wire Jan 8, 2016 In our short series last year, we outlined how machine learning can be used to detect new, never before seen types of fraud. By combining machine learning with big data and Hadoop, it is now possible to monitor massive amounts of data in real time and detect anomalies faster than ever before.
To create this list of machine learning influencers, we used the Twitter application LittleBird. The app has a feature called insiders, which calculates how connected a Twitter user is in regards to particular topics. It rates insiders based on how many of the other insiders follow that individual. Here are the top machine learning influencers of 2015: Rank Name Twitter Handle Followers Company 1 Andrew Ng @andrewyng 46.1K Chief Scientist, Baidu Inc.
2 Hilary Mason @hmason 66.8K Founder, Fast Forward Labs
3 Yann LeCun @ylecun 13.6K Director of AI Research, Facebook
4 Andrej Karpathy @karpathy 13.7K Computer Science PhD Student, Stanford
5 Gregory Piatetsky @kdnuggets 45.9K President, KDnuggets
6 Kirk Borne @kirkdborne 54.4K Principal Data Scientist, Booz Allen Hamilton
7 Olivier Grisel @ogrisel 12.6K Software Engineer, Inria
8 Randy Olson @randal_olson 78.3K Postdoctoral researcher, UPenn
9 John Myles White @johnmyleswhite 14.3K Scientist, Facebook
10 Peter Skomoroch @peteskomoroch 27K Startup Co-‐Founder and CEO
11 Andreas Mueller @t3kcit 7.1K Assistant Research Scientist, NYU
12 Ben Lorica @bigdata 29.3K Chief Data Scientist, O’Reilly Media
13 Jeff @hackingdata 24.5K Founder, Cloudera
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14 Wes McKinney @wesmckinn 14K Software Engineer, Cloudera
15 Richard Socher @RichardSocher 4.5K CEO, Metamind
16 Ryan Rosario @datajunkie 12.8K Statistics PhD Candidate, UCLA
17 Drew Conway @drewconway 14.8K Founder and CEO, Alluvium
18 Nando de Freitas @NandoDF 4.1K Deep Mind Scientist, Google
19 David Smith @revodavid 17.8K R Community Lead, Microsoft
20 Fei-‐Fei Li @drfeifei 5.2K Professor of Computer Science, Stanford
Graphic: LittleBird’s graphical representation of how influencers are connected to each other shows that they can be broken into different communities. The turquoise cluster connects people involved in machine learning at research universities, the magenta cluster is focused around San Francisco, while the gold cluster is split between London and San Francisco.