Recommender systems and high-frequency trading (Practical AI #126)

David Sweet, author of “Tuning Up: From A/B testing to Bayesian optimization”, introduces Dan and Chris to system tuning, and takes them from A/B testing to response surface methodology, contextual bandit, and finally bayesian optimization. Along the way, we get fascinating insights into recommender systems and high-frequency trading!

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Featuring:

• David Sweet – LinkedIn, X
• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

Books

• “Experimentation for Engineers” by David Sweet
  • Tuning Up | GitHub
  • Manning 40% discount code: podpracticalAI19

Something missing or broken? PRs welcome!