An intro to Probabilistic Programming with Ubers Pyro episode artwork

EPISODE · Nov 10, 2017 · 8 MIN

An intro to Probabilistic Programming with Ubers Pyro

from Siraj Raval

Probabilistic programming languages are built to harness the predictive power of probability distributions. Instead of making them a feature, they use these distributions as primitives with their own set of operands that allow for the creation of stochastic control flows. Since the real world is full of uncertainty, this type of thinking is useful to help build better AI systems. I'll use Uber's newly released Pyro tool to demonstrate how they work. Code for this video (with coding challenge): https://github.com/llSourcell/an_intro_to_probabilistic_programming Shannon's winning code: https://github.com/DecentricCorp/Coval-Unspecified-Ml-Blockchain Please Subscribe! And like. And comment. That's what keeps me going. Want more inspiration & education? Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://media.nips.cc/Conferences/2015/tutorialslides/wood-nips-probabilistic-programming-tutorial-2015.pdf http://probabilistic-programming.org/wiki/Home https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers https://www.oreilly.com/ideas/probabilistic-programming https://www.oreilly.com/learning/probabilistic-programming-from-scratch http://pyro.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/

Episode metadata supplied by the publisher feed · Published Nov 10, 2017

Probabilistic programming languages are built to harness the predictive power of probability distributions. Instead of making them a feature, they use these distributions as primitives with their own set of operands that allow for the creation of stochastic control flows. Since the real world is full of uncertainty, this type of thinking is useful to help build better AI systems. I'll use Uber's newly released Pyro tool to demonstrate how they work. Code for this video (with coding challenge): https://github.com/llSourcell/an_intro_to_probabilistic_programming Shannon's winning code: https://github.com/DecentricCorp/Coval-Unspecified-Ml-Blockchain Please Subscribe! And like. And comment. That's what keeps me going. Want more inspiration & education? Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://media.nips.cc/Conferences/2015/tutorialslides/wood-nips-probabilistic-programming-tutorial-2015.pdf http://probabilistic-programming.org/wiki/Home https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers https://www.oreilly.com/ideas/probabilistic-programming https://www.oreilly.com/learning/probabilistic-programming-from-scratch http://pyro.ai/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/

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An intro to Probabilistic Programming with Ubers Pyro

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Probabilistic programming languages are built to harness the predictive power of probability distributions. Instead of making them a feature, they use these distributions as primitives with their own set of operands that allow for the creation of...

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