Description (Parts 1 and 2): Introduction of neural network programming concepts, theory and techniques. The class material will being at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate concepts.
Description (Part 3): This part will continue the development of the neural network programming approaches from Parts 1 & 2. This part will focus on methods used to generate sequences: LSTM networks, sequence-to-sequence networks, and transformers.
Teacher: Erik Spence (SciNet, University of Toronto)
Level: Introductory
Format: Lecture + Hands-on
Certificate: Attendance
Prerequisites:
- Experience with Python will be assumed. (This course is being taught assuming this.)
- No prior experience with the Keras neural framework is expected. (The Keras neural framework will be used for neural network programming.)