Neural Foundations of Machine Learning

Neural Foundations of Machine Learning
Fall 2025 (GT Metz)

Topics

Projects

Course Material Overview

The class is divided into two exams, and five projects.

	Topic	Exam	Proj	On-Line Lectures	Reading
Week 1 Aug 18	Course Overview History of NN Digital ODE solutions		Proj1	ODE basics Matrix ODEs Nonlinear f( )
Week 2 Aug 25	Introduction to Neuroscience and Circuits			NN -- Neurons NN & Current Neuron Membrane Bio & FET Channel FET Bio Channel Linear Elements Circuit Anal 1^st Circuits Dynamics HighPass 1^st Order Energy Eff and Phys Compute Intro to Phys Compute
Week 3 Sept 1	Neuroscience, ODEs, Hopfield Networks		Proj2	Hopfield I	1^st Paper (1982) 1^st TSP (1985)
Week 4 Sept 8	Exam Prep	Sept
Week 5 Sept 15	Unsupervised learning			Unsupervised I Oja's Rule	Oja Alg (1982)
Week 6 Sept 22	Unsuper learning & Receptive Fields		Proj3		SOM (2013)
Week 7 Sept 29	Winner-Take All, Attention				Lazzaro 1988 Visual Att (1998)
Week 8 Oct 6	Adaptive Filters Perceptrons, WTA, VQ			Adapt Filt I Adapt Filt II Adapt Filt III	WTA 1 (2000)
Week 9 Oct 13	Supervised Learning Neural structures Backpropagation		Proj4		NN Work (1987) NN Gener (1989)
Week 10	Exam Prep	Oct
Break Week	Oct 27-31 .
Week 11	Neuroscience & Larger Networks		Proj5
Week 12	Conv NN & Deep NN
Week 13	Neuro Feedback Generative NN				GAN (2014)
Week 14	ML Physical Implementations

Projects are to be submitted electronically by 11:59pm Metz time

Last projects is due on ( ), submitted electronically by 11:59pm Metz time

Additional Material:

Datasets: A set of MATLAB datasets for Deep Learning. A link in the table to the main page gives the copy command to run the example file.
What is a neural network? Chapter 1, Deep learning https://youtu.be/aircAruvnKk

NN Playground from Google. A useful visualization of a simple NN structure.

Additional circuit related material