Recommender systems and high-frequency trading
No se pudo agregar al carrito
Solo puedes tener X títulos en el carrito para realizar el pago.
Add to Cart failed.
Por favor prueba de nuevo más tarde
Error al Agregar a Lista de Deseos.
Por favor prueba de nuevo más tarde
Error al eliminar de la lista de deseos.
Por favor prueba de nuevo más tarde
Error al añadir a tu biblioteca
Por favor intenta de nuevo
Error al seguir el podcast
Intenta nuevamente
Error al dejar de seguir el podcast
Intenta nuevamente
-
Narrado por:
-
De:
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!
Sponsors:
- O'Reilly Media – Learn by doing — Python, data, AI, machine learning, Kubernetes, Docker, and more. Just open your browser and dive in. Learn more and keep your teams’ skills sharp at oreilly.com/changelog
- RudderStack – Smart customer data pipeline made for developers. RudderStack is the smart customer data pipeline. Connect your whole customer data stack. Warehouse-first, open source Segment alternative.
- Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with no ads, extended episodes, outtakes, bonus content, a deep discount in our merch store (soon), and more to come. Let’s do this!
- Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com.
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
Upcoming Events:
- Register for upcoming webinars here!
Todavía no hay opiniones