NLP - Natural Language Processing

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Index - Natural Language Processing §

Book: slp3

Topics §

• Basics and preliminary knowledges
  • NLP - Lecture - Introduction
  • NLP - Lecture 2,3 - Elements of Linguistics
  • NLP - Lecture 4 - Corpora and Text Processing
  • NLP - Lecture 5 - Text Processing - Regular Expression, Eliza, NLTK
  • NLP - Lecture - Language Models, N-Grams, Perplexity
• Text Representation
  • NLP - Lecture - Text Representation
  • NLP - Lecture - Vector Space Models - Co-occurence matrix, TF-IDF, PMI
  • NLP - Lecture - Static Word Embeddings
• NLP tasks and classical approaches
  • NLP - Lecture - Text Classification Sentiment Analysis
  • NLP - Lecture - Neural Network for Text Classification and Language Modelling
  • NLP - Lecture - Machine Translation
  • NLP - Lecture - Spelling Correction
  • NLP - Lecture - Part-of-Speech Tagging (POS) and Named Entity Recognition (NER)
• Modern approaches and architectures
  • NLP - Lecture - Sequence Models, RNN, LSTM, Encoer-Decoder in NLP
  • NLP - Lecture - Transformers for NLP
  • NLP - Lecture - MaskedLM
  • NLP - Lecture - Large Language Models (LLM)

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Exam’s project §

• Project Hub - Language Modelling and Text Generation with RNNs and Attention empowered by PyTorch (EPIC FAIL)
• Project Hub - Tweet Emotion Classification

What the teacher want: a google colab notebook where you describe the problem mixing text and code.

Run the code, produce the output and comment the output.

Decide the parameter and train the architecture, you know what you have to modify and so on. “do what all the world does”.

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