ECE284
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ECE 284 - THEORETICAL MACHINE LEARNING
Electrical and Computer Engineering
College of Engineering
Full Course Title
THEORETICAL MACHINE LEARNING
Instructor Name(s)
PEDARSANI
Course Description
This course studies the mathematical foundations of machine learning, and focuses on understanding the trade-offs between statistical accuracy, scalability, and computation efficiency of distributed machine learning and optimization algorithms. Topics include empirical risk, convexity in learning, convergence analysis of gradient descent algorithm, stochastic gradient descent, neural networks, and reinforcement learning.
Unit Value
4
Maximum number of times course can be repeated for additional credit
0
Maximum Units
4
Recommended Preparation
ECE 235 or equivalent.