Post written by Sandhya Prabhakaran:
Firstly, I would like to thank MLConf and NYC Women in Machine Learning & Data Science for giving me the opportunity to attending this informative, educational and cutting-edge conference. I would also like to thank all the conference sponsors that made this event possible: http://mlconf.com/events/new-york-city-ny/.
The session brought together leading data scientists and software developers involved in applying ML algorithms for industrial applications. Talks dealt with improving traditional ML algorithms for handling online and large datasets to exploring distributed and scalable platforms such as the Microsoft Azure platform.
Here are some highlighted talks. Edo Liberty from Yahoo presented a distributed, streaming computational model for online data that is used for online portfolio management, online advertising and the Yahoo Finance app.
Jennifer Marsman from Microsoft proudly wore the EPOC headset from Emotive that captures EEG signals while demonstrating her online lie detector.
Sergei Vassilvitskii from Google discussed k-means++ which is k-means with tricks to handle large datasets. Lei Yang from Quora explained the big and ‘rich’ data Quora handles and the data challenges and algorithms used at Quora. Geetu Ambwani from Huffington Post introduces the ML challenges faced by the biggest social publisher.
Braxton McKee from Ufora asks programmers not to rewrite code to suit high-dimensional data but rather use his Pyfora software that learns information from source code to make it scalable.
Samantha Kleinberg from Stevens Institute of Technology emphasised the importance of causal factors in any event than just relying on correlation alone.
For a detailed event summary, please check here.
(Photo credits: MLconf on Facebook)