CSCI 456-01, Spring 2026: Schedule

	Date	Topic	Overview	To do
0	1/21	Introduction	Course logistics What CSCI 456 is about What LLMs are (and are not)
1	1/26	Class snowed out ❄️ ❄️ ❄️
2	1/28	N-grams	Conditional probability The N-gram model Entropy, cross-entropy, & perplexity	For further reading: Claude Shannon, A mathematical theory of communication , 1948. Claude Shannon, Prediction and entropy of printed English , 1951.
3	2/2	Preprocessing	Normalization Tokenization	Homework, due Wednesday, February 11: Entropy, cross-entropy, and perplexity. You will need the the file https://www.cs.wm.edu/~rml/teaching/csci456/hw/perplexity.zip, which I forgot to post earlier. It contains `american.txt`. Building an N-gram model.
4	2/4	Neural networks	Feed-foward networks Word embeddings and word2vec RNNs	Reading: Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean, Efficient Estimation of Word Representations in Vector Space . Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean Efficient Estimation of Word Representations in Vector Space Ilya Sutskever, Oriol Vinyals, Quoc V. Le, Sequence to Sequence Learning with Neural Networks .