Machine Learning with BigML

Poul Petersen (http://www.linkedin.com/pub/poul-petersen/0/36b/9b2) told me that he is coming to Austin for the AAAI-15 conference, so I asked if he could spare an evening to tell us about what he is doing at BigML (http://www.bigml.com). These folks have been speaking at conferences around the country, but this will be their first trip to Austin.

The Abstract

Traditionally, machine learning tools have been prohibitively complex and expensive – affordable only to large corporations, and usable only by highly trained technicians and consultants. In addition, they’ve lacked the programmability and flexibility aspects required to incorporate these learning strategies into related applications and services.

To address this problem, the BigML (http://www.bigml.com) team has been working hard for the past several years to democratize machine learning – making it more consumable, programmable, and scalable. The net result is an extremely powerful yet intuitive platform that can be leveraged equally by business analysts, developers and data scientists who are eager to perform a variety of predictive analytics and machine learning tasks.

In this session Poul will show how BigML employs its well-defined workflow, visualizations, and fully featured REST API to makes machine learning more accessible. Concepts demonstrated will include predictive analytics with decision trees, how to solve over-fitting with ensembles, how to evaluate a predictive model, how to find patterns with clustering and how to detect anomalies.

About the speaker

Poul Petersen (http://www.linkedin.com/pub/poul-petersen/0/36b/9b2) is BigML’s Chief Infrastructure Officer and has an MS degree in Mathematics as well as BS degrees in Mathematics, Physics and Engineering Physics. With over 20 years of experience building scalable and fault tolerant systems in data centers, Poul currently enjoys the benefits of programmatic infrastructure, hacking in python to runBigML’s infrastructure with only a laptop and a cloud.

Agenda:

6:30pm - networking
7:00pm - announcements
7:15pm - Featured presentation / Q&A