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Talking Machines: Computational learning theory and machine learning for understanding cells, with Aviv Regev
Stem cell. Source: CC0
In episode ten of season two, we talk about Computational Learning Theory and Probably Approximately Correct Learning originated by Professor Leslie Valiant of SEAS at Harvard, we take a listener question about generative systems, plus we talk with Aviv Regev, Chair of the Faculty and Director of the Klarman Cell Observatory and the Cell Circuits Program at the Broad Institute.
If you like this podcast, you may also be interested in:
- Talking Machines: Women in Machine Learning, with Hanna Wallach
- Talking Machines: Gaussian processes and OpenAI, with IIya Sutskever
- Talking Machines: Real human actions and Women in Machine Learning (WiML), with Jenn Wortman Vaughan
- Talking Machines: Machine learning in healthcare and the AlphaGo matches
- Talking Machines: AI safety and the legacy of Bletchley Park, with Nick Patterson
- Talking Machines: Robotics and machine learning music videos, with Michael Littman
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tags: Talking Machines
Talking Machines
is your window into the world of machine learning.
Talking Machines
is your window into the world of machine learning.
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