MLconf NYC 2016

MLconf was created to host the thought leaders in Machine Learning and Data Science to discuss their most recent experience with applying techniques, tools, algorithms and methodologies to the seemingly impossible problems that occur when dealing with massive and noisy data. MLconf is independent of any outside company or university – it’s simply a conference organized to gather the Machine Learning communities in various cities to share knowledge and create an environment for the community to coalesce.

Event Speakers:

Kaheer Suleman, CTO, Maluuba

Abstract: Conversational Language Understanding

Jennifer Marsman, Principal Developer Evangelist, Microsoft

Abstract: Using EEG and Azure Machine Learning to Perform Lie Detection

Soumith Chintala, Artificial Intelligence Research Engineer, Facebook

Abstract: Predicting the Future Using Deep Adversarial Networks: Learning With No Labeled Data

Erich Elsen, Research Scientist, Baidu

Abstract: Training Recurrent Neural Networks at Scale

Sergei Vassilvitskii, Research Scientist, Google

Abstract: Teaching K-Means New Tricks

Braxton McKee, CEO & Founder, Ufora

Abstract: Say What You Mean: Scaling Machine Learning Algorithms Directly from Source Code

Geetu Ambwani, Principal Data Scientist, Huffington Post

Abstract: Data Science in the Newsroom

Edo Liberty, Research Director, Yahoo

Abstract: Online Data Mining: PCA and K-Means

Lei Yang, Senior Engineering Manager, Quora

Abstract: Sharing and Growing the World's Knowledge with Machine Learning

Samantha Kleinberg, Assistant Professor of Computer Science, Stevens Institute of Technology

Abstract: Casual Inference and Explanation to Improve Human Health

Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consulting

Abstract: Scripts that Scale with F# and mbrace.io

Damien Lefortier, Senior Machine Learning Engineer and Tech Lead in the Prediction Machine Learning team, Criteo

Abstract: Machine Learning for Display Advertising @ Scale

Yael Elmatad, Senior Data Scientist, Tapad

Abstract: Beyond the Classifier, Inspiration from Engineering Algorithms

Furong Huang, Ph.D. Canidate, UC Irvine

Abstract: Discovery of Latent Factors in High-dimensional Data Using Tensor Methods

Ike Nassi, Founder, TidalScale

Abstract: Scaling Spark - Vertically

Michael Galvin, Sr. Data Scientist, Metis

Abstract: An Introduction to Word2vec and Working With Text Data

Welch Labs, Short Tutorial Videos on Mutual Information & Decision Trees

Sponsors:

Gold: Metis, Cloudera, Dato, Meetup.com, Quora, SAS Inc, Cubist Systematic Strategies

Silver: Google, Baidu Research, h2o.ai, HiringSolved

Bronze: Maluuba, Facebook Research

Media: O'Reilly, CRC Press, MIT Press, Now Publishers, Cambridge University Press, Galvanize, Springer