The TWIML AI Podcast

@twimlai

This Week in & (podcast) brings you the week’s most interesting and important stories from the world of and artificial intelligence.

Vrijeme pridruživanja: svibanj 2016.

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  1. proslijedio/la je Tweet

    It was a pleasure. Thanks for having me on! :D

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  2. prije 20 sati

    Today we’re joined by Bob Killen (), Research Cloud Administrator at , to discuss how Bob and his group are deploying , the internal user experience, how they're taking advantage of distributed computing and

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  3. proslijedio/la je Tweet
    prije 24 sata

    It is certain that correlation is not causality. But then, what is? And how to represent it? A fascinating talk on the edge of current AI topics. via thank you

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  4. 1. velj

    In episode #342 of The Pod, Robert Ness joins us to talk all things Causality, including the philosophy behind it, causal inference, real-world applications and much more. Check it out at !

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  5. 31. sij

    ICYMI, on the latest episode of the podcast we're joined by and of , to talk , their structured programming and distributed processing platform. Check it out at .

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  6. 31. sij

    Put it in your calendar! Tomorrow at 8am PT we kick off our Causal Modeling in Machine Learning study group with an overview/preview session, hosted by and . More info at . You won't want to miss it!

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  7. proslijedio/la je Tweet
    31. sij

    Hey everyone, I'm so excited to share my recent interview on Scalable and Maintainable Workflows at Lyft with Flyte with for the podcast. Check it out! via

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  8. proslijedio/la je Tweet
    31. sij

    My heart jumps to see these IMHO essentially philosophical discussions in ML related papers. Galilei and other giants on whose shoulders we walk would be delighted. Thanks for sharing this gem.

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  9. proslijedio/la je Tweet
    31. sij

    episode on . The flytekit SDK is probably the coolest part of the project.

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  10. proslijedio/la je Tweet
    30. sij
    Odgovor korisnicima

    Thanks for sharing, Travis! Differential privacy and privacy-preserving ML are topics I think we'll be hearing a lot more about in the upcoming months/years! cc

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  11. 30. sij

    Today we kick off our ‘19 series joined by and of . In our conversation, we discussed their open-sourced, cloud-native ML and data processing platform, Flyte, and how it is used across Lyft.

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  12. proslijedio/la je Tweet
    30. sij

    Learnt a lot from podcast on , a way of collecting about the population while protecting the privacy of individual users by adding noise to the data 🔏here's the podcast:

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  13. 29. sij

    Check out the latest episode of The Podcast, where we're joined by Robert Ness, creator of the course Causal Modeling in Machine Learning, and host of the upcoming study group on the topic!

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  14. proslijedio/la je Tweet
    29. sij

    If you're interested in , is hosting a study group led by . I also recommend 's "Causal Data Science" series of articles on Medium... among other things.

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  15. proslijedio/la je Tweet
    29. sij

    A summary of a few recent worthwhile listens on the podcast: ... much appreciated for the great content!

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  16. proslijedio/la je Tweet
    28. sij

    Uh oh - more nightshifts coming up in 2020! 😉Just got the invite for the upcoming live course. 🧡 Thanks and crew - 👍Is the crew ready, too?

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  17. proslijedio/la je Tweet
    27. sij

    Today Robert Ness (), ML Research Engineer at and Instructor at , joins to discuss Causality, and our upcoming study group based around his new course sequence, “Causal Modeling in Machine Learning.”

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  18. proslijedio/la je Tweet
    28. sij

    Terrific podcast here on ML & causal learning considerations. Would suggest that causal modeling has some near term non-systemic value propositions associative to predicting interventions as well.

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  19. proslijedio/la je Tweet
    28. sij

    String together.. Statistics, Markov chain, entropy, causality, system thinking, stochastic modeling, observer effects, causal inference, change, vector sates... I'm a soft tissue blob stuck to a n-dimensional space time manifold every-time someone talks about causality.

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  20. 27. sij

    Today Robert Ness (), ML Research Engineer at and Instructor at , joins to discuss Causality, and our upcoming study group based around his new course sequence, “Causal Modeling in Machine Learning.”

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