Making reinforcement learning practical for real-world developers

"Building machine learning-enabled products are hard for developers and data scientists; throw in a hardware component, and the complexity increases exponentially. Sunil Mallya walks you through how to build complex ML-enabled products using RL, explores hardware design challenges and trade-off...

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Detalles Bibliográficos
Otros Autores: Mallya, Sunil, on-screen presenter (onscreen presenter)
Formato: Vídeo online
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media 2019.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009822836806719
Descripción
Sumario:"Building machine learning-enabled products are hard for developers and data scientists; throw in a hardware component, and the complexity increases exponentially. Sunil Mallya walks you through how to build complex ML-enabled products using RL, explores hardware design challenges and trade-offs, and details real-life examples of how any developer can up level their RL skills through autonomous driving. This session is from the 2019 O'Reilly Artificial Intelligence Conference in San Jose, CA. and is sponsored by Amazon Web Services."--Resource description page.
Notas:Title from title screen (viewed July 22, 2020).
Descripción Física:1 online resource (1 streaming video file (42 min., 36 sec.)) : digital, sound, color