Morning I — 9:30 to 10:45 — Data analysis I

An introductory session covering the basic ideas behind neural networks, especially the function and distribution approximation property. This will be followed by a toy problem of linear regression using neural-networks.

Intro slides

Tutorial on neural networks as approximators

Bayesian inference toy problem: linear regression


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