Morning I — 9:30 to 10:45 — Data analysis I
Location: Bhaskara 3, IUCAA
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 (link)
Tutorial on neural networks as approximators
Bayesian inference toy problem: linear regression
Material is provided in this repository. It is recommended that you create your environment before the session. Instructions are in the README under the link.