Machine Learning and Pattern Recognition
ECE 435
1252
1252
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This course is an introduction to the theoretical foundations of machine learning. A variety of classical and recent results in machine learning and statistical analysis are discussed, including: classification, regression, regularization, optimization, gradient descent,
neural networks, convolutional networks, and reinforcement learning.
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Section L01
- Type: Lecture
- Section: L01
- Status: O
- Enrollment: 50
- Capacity: 65
- Class Number: 21462
- Schedule: MWF 10:00 AM-10:50 AM - Thomas Laboratory 003