Machine Learning Interviews

by vyolian

I’ve been fairly busy lately and I have a backlog of blogs to write — mostly about startups. But since I don’t have much time, I’m going to cheat a little and link to a project that I’m pretty excited about.

I’ve been attracting a community of machine learning folks from around the web at http://machine-learning.eggsprout.com. It came to mind that interviews are a great way to learn about someone very quickly. It’s also an awesome way to generate unique and valuable content. I love doing it and it gives me an excuse to reach out to people I never would have otherwise.

Here’s a couple I’ve done so far and I’ll add to this list as I get more. I have a series of interviews for machine learning professionals as well as one for machine learning hiring companies. Please get in contact with me if you’d be open to an informal, flexible, email interview with me!

* Udi Schlessinger, ML + Evolutionary Computation (part 2)

The problem with evolutionary algorithms and machine learning is that it is really hard to create super-large neural networks (think millions or billions of nodes), however, using development this might be possible. If biology does it, so can we!

* Brian Donhauser, Financial Econometrician & ML Fanboy

People in financial economics have used the non-linear techniques found in ML to forecast asset returns, volatilities, correlations, etc., with varying degress of success. What I’m doing with high-frequency data would be considered more of a pre-processing step in knowledge discovery.

* John Graham-Cumming, Causata CTO

Secondly, many machine learning models are non-real time. Information about relationships is built using batch processes and presented to users later. Causata performs real-time machine learning which creates a number of challenges for our developers