| Type | Filename  | Size | Date | |
|---|---|---|---|---|
| Lab 1 (N-gram Language Models) Introduction to the NLTK library. Tokenization and N-gram Language Models (LMs). Cross-entropy and perplexity of LMs. Part-of-speech (POS) tagging, stemming. Beam-search decoding. | 570.51 KB | 4/11/24 | ||
| Lab 2 (mostly Linear Models) Introduction to the scikit-learn library. Text classification with both linear & non-linear classifiers. Lazypredict library. Learning curves. Pipelines and hyper-parameter tuning via grid or randomized search. | 622.97 KB | 4/23/24 | ||
| Lab 3 (MLPs) Introduction to Keras and Keras Tuner. Text classification with MLPs using tf-idf and centroids of pretrained word2vec embeddings. Example with word2vec word embeddings with gensim. | 152.75 KB | 4/24/24 | ||
| Lab 4 (RNNs) Text classification with RNNs in Keras. Linear / deep self attention mechanisms. | 178.38 KB | 2/18/24 | ||
| Lab 5 (CNNs) Text classification with (multi-filter) CNNs in Keras. | 611.4 KB | 2/22/24 | ||
| Lab 6 (Transformers) Text classification with CNNs in Keras. Fine tuning BERT for text classification and NER (token classification) tasks using transformers library. | 75.31 KB | 2/29/24 | ||
| Lab 7 (Prompting) Short introduction to open-source LLMs and prompt engineering. | 1.4 MB | 3/27/24 |
