Course : M35209F/Μ36209P - Text Analytics (MSc AI & Data Science)

Course code : INF312

M35209F/Μ36209P - Text Analytics (MSc AI & Data Science)

INF312  -  Ion Androutsopoulos

Documents
Root directory in_class_demos_2025_26   Files for the in-class demos of 2025-26.
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First Name Size Date
Demo 1 (N-gram Language Models)
Introduction to the NLTK and spaCy modules. Tokenization and N-gram Language Models (LMs). Cross-entropy and perplexity of LMs. Beam-search decoding.
321.52 KB 4/29/26, 1:38 PM
Demo 2 (Text Classification w/ Mostly Linear Models)
Introduction to the scikit-learn library. Text classification with both linear & non-linear classifiers. Learning curves. Pipelines and hyper-parameter tuning via grid or randomized search.
899.28 KB 2/19/26, 6:50 PM
Demo 3 (Text Classification w/ MLPs)
Introduction to PyTorch. Text classification with MLPs using tf-idf vectors and centroids of pretrained word2vec embeddings. Example with word2vec word embeddings with gensim.
809.58 KB 5/15/26, 11:11 PM
Demo 4 (Text Classification w/ RNNs)
Text classification with RNN models in PyTorch.
135.95 KB 5/29/26, 9:23 PM
Demo 5 (Text Classification w_ CNNs).zip
Text classification with CNN models in PyTorch.
308.05 KB 6/12/26, 9:07 PM
Demo 6 (Introduction to Transformers)
Introduction to the HuggingFace library. Zero-shot inference and text classification/POS tagging with large pre-trained models. Fine-tuning with different approaches.
60.16 KB 6/19/26, 8:18 PM
Demo 7 (Agentic Applications examples)
Examples of application development using LLM agents. Introduction to LangChain, LangGraph, Groq and Gradio. Llama 3.1 8B parameter-efficient fine-tuning using LoRA adapters and inference using TGI.
146.12 KB 6/26/26, 8:38 PM