Introduction to Deep Learning

ECSE-6850

Deep learning fundamentals and applications in artificial intelligence. Topics include machine learning foundation, linear regression and classification, deep neural networks, convolutional neural networks, recurrent neural networks, generative adversary neural networks, Bayesian neural networks, deep Boltzmann machine, deep Bayesian networks, and deep reinforcement learning.

3 credits
Prereqs:
none

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2024
Intro To Deep Learning (3c)
  • Qiang Ji
Seats Taken: 26/30
2023
Intro To Deep Learning (3c)
  • Qiang Ji
Seats Taken: 16/30
2022
Intro To Deep Learning (3c)
  • Qiang Ji
Seats Taken: 23/30
2021
Intro To Deep Learning (3c)
  • Qiang Ji
Seats Taken: 16/30
2020
Intro To Deep Learning (3c)
  • Qiang Ji
Seats Taken: 25/30
2019
Intro To Deep Learning (3c)
  • Qiang Ji
Seats Taken: 27/40
2018
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