Interviews

Well, maybe. That’s what Sarah Braden did at MLconf in New York, in 2014. Now a busy data scientist at HireIQ, Braden credits the event for providing the forum needed to connect with startups hiring in machine learning.
“It’s harder to make contacts than it is to learn new skills and develop new areas of expertise,” Braden says. “I used MLconf to meet new people.”
Braden counts the smaller size of MLconf as a big plus. “You get to have better interaction, and people remember you better. I’ve been to quite a few larger events. There’s so much going on—people are rushing to the next talk and don’t get to stop and have good conversation.”
A PhD in geological sciences with a specialty in planetary sciences, Braden cut her research teeth using a lunar reconnaissance orbiter camera to study young lunar volcanism. After earning her degree, she taught herself Python programming as an entry into data science. “I was very motivated to learn these skills, and there’s a great demand in the industry right now,” she says.
At MLconf, she approached HireIQ during a networking break. “I found out we had some common background; for instance, the CTO had experience with satellite engineering. Through talking with them, I found a connection.”
After the event, Braden followed up to see if they might be interested in hiring her, and the professional link was born. “I think it’s really about the culture fit,” she explains, “If I hadn’t seen them at MLconf, I wouldn’t have known about them.”
Now Braden fills her days working on HireIQ’s automated interview technology, collecting data for predicting whether candidates will stay at a job. She also communicates the value of machine learning to clients as “something that can help them in their business models and help the efficiency of their recruiters.”
Braden plans to return to MLconf in New York this month—and to a future event as a speaker. “I’m hoping to speak on feature extraction and modeling from data collected from speech-to-text algorithms.”
Tips for aspiring data scientists:
If you’re a student or an aspiring data scientist attending MLconf, Braden advises:

• Have a strong understanding of programming, statistics, and basic data science concepts before you go.
• Bring business cards so people can stay in touch.
• Research the speakers beforehand to get the most out of the talks and to keep up, since a lot of the info is new.
• Don’t be afraid to introduce yourself to companies and attendees.
• Follow up with new contacts after the conference.

—Natasha Petroff
Natasha Petroff is a senior writer at Kitterman Marketing. Kitterman is a marketing and advertising agency that blends strategic messaging and creative with the latest technology and analytics to create campaigns that deliver measureable results.

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.