aivancity NLP#
Main repository for the 2024-2026 Natural Language Processing class at aivancity by Paul Lerner (both during semester 1 and 2)
Classes (2025-2026)#
Classes (2024-2025)#
Practical Works (2025-2026)#
- Practical Work 1: Text Classification/Bag of Words/Naive Bayes https://colab.research.google.com/github/LernerPaul/pw1_cls/blob/main/notebook.ipynb 
- Practical Work 2: Distributional Semantics/Skipgram/word2vec https://colab.research.google.com/github/LernerPaul/pw2_embedding/blob/master/notebook.ipynb 
Practical Works (2024-2025)#
- Practical Work 2: Transformers https://colab.research.google.com/github/PaulLerner/aivancity_nlp/blob/main/pw2_transformers.ipynb 
- Practical Work 3: Large Language Models https://colab.research.google.com/github/PaulLerner/aivancity_nlp/blob/main/pw3_llm.ipynb 
- Practical Work 4: Information Extraction https://colab.research.google.com/github/PaulLerner/aivancity_nlp/blob/main/pw4_eval_ie.ipynb 
Contributing#
Add Google Colab badges to PWs with https://openincolab.com/
Build docs using sphinx-build -b html . docs
Acknowledgements#
This class directly builds upon:
- Jurafsky, D., & Martin, J. H. (2024). Speech and Language Processing : An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition with Language Models (3rd éd.). https://web.stanford.edu/~jurafsky/slp3/ed3bookaug20_2024.pdf 
- Eisenstein, J. (2019). Natural Language Processing. 587. https://nlp.cs.princeton.edu/cos484-sp21/readings/eisenstein-nlp-notes.pdf 
- Yejin Choi. (Winter 2024). CSE 447/517: Natural Language Processing (University of Washington Paul G. Allen School of Computer Science & Engineering) 
- Noah Smith. (Winter 2023). CSE 447/517: Natural Language Processing (University of Washington Paul G. Allen School of Computer Science & Engineering) 
- Benoît Sagot. (2023-2024). Apprendre les langues aux machines (Collège de France) 
- Chris Manning. (Spring 2024). Stanford CS224N: Natural Language Processing with Deep Learning 
- Classes where I was/am Teacher Assistant: - Christopher Kermorvant. Machine Learning for Natural Language Processing (ENSAE) 
- François Landes and Kim Gerdes. Introduction to Machine Learning and NLP (Paris-Saclay) 
 
Also inspired by:
- My PhD thesis: Répondre aux questions visuelles à propos d’entités nommées (2023) 
- Noah Smith (2023): Introduction to Sequence Models (LxMLS) 
- Kyunghyun Cho: Transformers and Large Pretrained Models (LxMLS 2023), Neural Machine Translation (ALPS 2021) 
- My former PhD advisors Olivier Ferret and Camille Guinaudeau and postdoc advisor François Yvon 
- My former colleagues at LISN