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    Sayak Paul

    Sayak Paul

    FromMachine Learning Street Talk (MLST)

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    Sayak Paul

    FromMachine Learning Street Talk (MLST)

    ratings:
    Length:
    96 minutes
    Released:
    Jul 17, 2020
    Format:
    Podcast episode

    Description

    This week we spoke with Sayak Paul, who is extremely active in the machine learning community. We discussed the AI landscape in India, unsupervised representation learning, data augmentation and contrastive learning, explainability, abstract scene representations and finally pruning and the recent super positions paper. I really enjoyed this conversation and I hope you folks do too!

    00:00:00 Intro to Sayak
    00:17:50 AI landscape in India
    00:24:20 Unsupervised representation learning
    00:26:11 DATA AUGMENTATION/Contrastive learning
    00:59:20 EXPLAINABILITY
    01:12:10 ABSTRACT SCENE REPRESENTATIONS
    01:14:50 PRUNING and super position paper
    Released:
    Jul 17, 2020
    Format:
    Podcast episode

    Titles in the series (100)

    This is the audio podcast for the ML Street Talk YouTube channel at https://www.youtube.com/c/MachineLearningStreetTalk Thanks for checking us out! We think that scientists and engineers are the heroes of our generation. Each week we have a hard-hitting discussion with the leading thinkers in the AI space. Street Talk is unabashedly technical and non-commercial, so you will hear no annoying pitches. Corporate- and MBA-speak is banned on street talk, "data product", "digital transformation" are banned, we promise :) Dr. Tim Scarfe, Dr. Yannic Kilcher and Dr. Keith Duggar.