Meta-Learning 5th Ed

About the Course: 

Topics covered in lectures will be as follows:

1. Meta-Learning: Introduction and Motivation

2. Unsolved  Challenge problems: Numerai & ARC

3. Optimisation, Metric and Model based Meta-learning

4. Neuro-symbolic Program Synthesis for ARC

5. Large Language Models as Meta-learners

Pre-requisites: 

(i) Must have already taken and cleared, or be currently enrolled in a machine-learning or related course e.g., statistical machine-learning, deep-learning,  reinforcement-learning, etc.

(ii) Familiarity with object-oriented programming in python and use of pandas

(iii) Familiarity with coding and training neural networks in pytorch