Our past Technical Chair and I recently spoke with Lon Riesberg, of Data Elixir, regarding The Machine Learning Conference. As MLconf considers itself a community event, we found Data Elixir to be a great newsletter/information hub for the machine learning community. Check out our conversation below!
Lon: Why did you start MLconf?
Courtney: The Machine Learning Conference (MLconf) began in 2012, as a partnership with Carnegie Mellon University’s GraphLab team, to gather the thought leaders in Machine Learning, specifically Graph Databases. In 2013, MLconf became a separate event, devoted to the Machine Learning and Data Science community in San Francisco, agnostic of any tool, platform or company. MLconf events host speakers from various industries, research and universities to discuss recent research and application of Machine Learning methodologies and practices. In 2014, MLconf entered NYC and Atlanta, as well as San Francisco. In 2015, MLconf will host conferences in NYC, Atlanta, Seattle and San Francisco, with plans to enter additional US cities in 2016, and the UK.
Lon: Who’s the ideal attendee?
Technical Chair: We usually try to answer the opposite question; how can we be ideal for people who want to keep in touch with what is happening in machine learning. From our registration statistics (yes we also do machine learning) we see that our attendees are data scientists focused on the machine learning aspect, engineers or Phds who are transitioning to datascience, grad students and some executives/Venture Capitalists. Attendees typically attend MLconf, to enjoy a quick, one-day conference that includes talks from companies like Google, Yahoo, Netflix, etc or other upcoming startups that present on what algorithms, methods and tools have already been tested and proved efficient.
Lon: Who are the presenters? (e.g. typical backgrounds, some well-known presenters)
Technical Chair: The presenters are Research Scientists/Engineers and Professors. Some of them are machine learning veterans like Corinna Cortes from Google Research as well as influencers like Claudia Perlich with industrial and academic backgrounds. MLconf events also host speakers with strong experience in complicated machine learning engineering implementations like Xavier Amartian from Quora (formerly Netflix). The MLconf program committee searches for people who have an interesting track record in machine learning and interesting topics to present. We spend a lot of time working with the presenters to make sure that the math level the style and the content meets the expectation of the audience. We absolutely do not allow presentations that are sales and marketing pitches, or make strong arguments that are disrespectful for the community. Every presentation should have a clear message, not heavy in mathematical details and references for further and deeper study if the audience wants to learn more.
Lon: What can attendees expect to get out of MLconf?
Courtney: MLconf offers busy professionals a quick and digestible day of presentations to help stay current on the application of machine learning tools and techniques within the community. Grad students may find certain presentations that influence their direction in their studies, they will learn about new tools/software and, of course, network with companies that are hiring. MLconf offers students a glance at what the Machine Learning methods are used in industry and how to pursue such professional experience within hiring organizations. Academic Professors seek collaboration to the industry and they often evangelize new algorithms and paradigms accompanied by open source software. Additional attendees benefit from the sharing of knowledge and networking during the extended lunch break and coffee breaks.
Lon: What do you hope for the future of MLconf?
Courtney: As I mentioned before, we want to cross the US borders and have MLconf hosted in European cities. In terms of the content and the format of the conference we are experimenting with new features. Last year we added the book exhibition where publishers contribute several ML books. This year we are adding the short talks that answer technical questions on machine learning topics. This year we launched a job search section on our website. In this free service, our goal is to smoothly and confidentially connect interested attendees with hiring companies within the community.
