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Talking Machines: Bias variance dilemma for humans and the arm farm, with Jeff Dean
In episode four of season three Neil introduces us to the ideas behind the bias variance dilemma (and how how we can think about it in our daily lives). Plus, we answer a listener question about how to make sure your neural networks don’t get fooled. Our guest for this episode is Jeff Dean, Google Senior Fellow in the Research Group, where he leads the Google Brain project. We talk about a closet full of robot arms (the arm farm!), image recognition for diabetic retinopathy, and equality in data and the community.
Fun Fact: Geoff Hinton’s distant relative invented the word tesseract. (How cool is that. Seriously.)
If you enjoyed this episode, you may also want to listen to:
- Talking Machines: Overfitting and asking ecological questions, with Tom Dietterich
- Talking Machines: Restricted Boltzmann Machines, with Eric Lander
- Talking Machines: Automatic Translation and t-SNE, with Hal Daume
- Talking Machines: Generative art and Hamiltonian Monte Carlo, with Doug Eck
- Talking Machines: Machine learning and the Flint water crisis, with Jake Abernethy
- Talking Machines: Gaussian processes and OpenAI, with IIya Sutskever
See all the latest robotics news on Robohub, or sign up for our weekly newsletter.
tags: c-Research-Innovation, Google, machine learning, 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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