The video presentation below is “Why Machine Learning Algorithms Fall Short (And What You Can Do About It)” by Jean-François Puget, speaking at MLconf SF 2016. Many think that machine learning is all about the algorithms. Want a self-learning system? Get your data, start coding or hire a PhD that will build you a model that will stand the test of time. Of course we know that this is not enough. Models degrade over time, algorithms that work great on yesterday’s data may not be the best option, new data sources and types are made available. In short, your self-learning system may not be learning anything at all.
This presentation examines how to overcome challenges in creating self-learning systems that perform better and are built to stand the test of time. You’ll see how to apply mathematical optimization algorithms that often prove superior to local optimization methods favored by typical machine learning applications and discuss why these methods can crate better results. You’ll also see the role of smart automation in the context of machine learning and how smart automation can create self-learning systems that are built to last.
The slides for the presentation can be found HERE.
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