Bayesian Optimization for Hyperparameter Tuning with Scott Clark - TWiML Talk #50

As you all know, a few weeks ago, I spent some time in SF at the Artificial Intelligence Conference. While I was there, I had just enough time to sneak away and catch up with Scott Clark, Co-Founder and CEO of Sigopt, a company whose software is focused on automatically tuning your model’s parameters through Bayesian optimization. We dive pretty deeply into that process through the course of this discussion, while hitting on topics like Exploration vs Exploitation, Bayesian Regression, Heterogeneous Configuration Models and Covariance Kernels. I had a great time and learned a ton, but be forewarned, this is most definitely a Nerd Alert show! Notes for this show can be found at twimlai.com/talk/50

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Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.