Quarter
Course Type
Location
ILP 2101
Units
4
Day and Time
M/W 12:30-1:45pm
Course Description

This course will be about modern artificial intelligence and machine learning. It will start with a general overview of five fundamental neural networks (MLP, CNN, RNN, Autoencoder and Transformer) and followed by discussions of text, image and video generation techniques.

Tentatively, topics may include the following: 
* CNN, RCNN, Fast RCNN, Faster RCNN, Yolo, Mask RCNN, 
* RNN and LSTM, 
* Attention and Transformer, Word2Vec, Elmo, Bert, and GPT, 
* PixelCNN/RNN, Autoencoder, Variational Autoencoder, and VQ VAE, 
* Diffusion models (Dall-e and Glide), 
* Flow-based generation, Nice, Real NVP, and Glow, 
* Generative and Adversarial Networks.  

Topics may be modified depending on the interests of the participants and current R&D directions. 

The minimum preparation is CMPSC 130B. CMPSC 165B is highly recommended but CMPSC 165A can serve as a substitute.