Genesis

di
  1. Percorso didattico pubblicato su GitHub: https://albarron.github.io/
  2. Testo: Natural language processing in action
  3. Articolo: Python for NLP: Creating a Rule-Based Chatbot
  4. Articolo: Unix for poets
  5. Applica il codice a un file di prova: genesis.txt

Python for poets

  1. p4p 1 (PDF)
  2. Lezione (YouTube)
  3. Notebook 1
  4. Notebook 2
  5. Notebook 3
  6. Notebook 4
  7. Notebook 5

Computational Linguistics

  1. Introduction to Computational Linguistics
    1. [25/02/21] Slides
  2. Words and vector space model
    1. [26/02/21] Slides on tokens
    2. [04/03/21] Notebook
    3. [05/03/21] Slides on tokens + RB sentiment
    4. [05/03/21] Notebook on extracting tokens
    5. [11/03/21] Notebook on rule-based sentiment analysis
  3. Naive Bayes
    1. [11/03/21] Slides on Naïve Bayes
    2. [12/03/21] Notebook on Naïve Bayes
  4. Word vectors
    1. [18/03/21] Slides on vectors and tf-idf
    2. [18/03/21] Notebook
  5. From Word Counts to Meaning
    1. [19/03/21] Slides introducing topic modeling
    2. [19/03/21] Notebook
  6. Training and Evaluation
    1. [25/03/21] Slides on training and evaluation
    2. [25/03/21] notebook
  7. Intermezzo
  8. Intro to LSA
    1. [08/04/21] Slides LSA and SVD
    2. [08/03/21] Notebook
  9. Intro to NN
    1. [09/04/21] Slides on the perceptron
    2. [09/04/21] Notebook on the perceptron
    3. [15/04/21] Slides introducing neural networks and keras
    4. [15/04/21] Notebook introducing neural networks and keras
  10. Word Embeddings
    1. [16/04/21] Slides on word2vec
  11. Visualisation
    1. 11. From document representations, towards sequences
  12. Convolutions for text
  13. Text is Sequential