Artificial Intelligence Engines
Second to follow.
Live lecture each Thursday at 11am-noon, 5, 12, 19, 26th November and 3rd December. The lecture for each week will review past week's topics and look forward to the coming week's material. All meetings will be on Teams.
(P# References below to pre-recorded videos; live-sessions (L#) will be recorded and uploaded also.)
Slides are available as 1-up and 4-up.
L1: Overview of course.
P2: Introductory neuroscience. Simple models.
P3: Perceptron.
L2: Code run throughs.
P4: Backprop.
P5: Backprop applications.
P6: Back prop derivation (two parts).
L3: code run through (backprop, keras, assignment 1)
P7: Dimensionality reduction.
P8: Tips and tricks/ recent advances.
P9: Convolutional neural networks (CNNs), images.
Live: assignment discussion.
P10: Hopfield networks.
P11: Boltzmann machines / RBMs / GANs.
P12: Sequences.
P13: Reinforcement learning.
P14: Unsupervised learning.
Example classes (3) likely to run over into Lent Term, possibly with second assignment.