ML for Social Science, Fall 2026
| Outline: |  | Book office hours: |  |
 |
Session 1: Workflow and ML regression | Interactive slides | Print slides (pdf) |
| R code: Quarto HTML | Python code: Jupyter Quarto HTML | ||
 |
Session 2: Classification | Interactive slides | Print slides (pdf) |
| R code: Quarto HTML | Python code: Jupyter Quarto HTML | ||
 |
Session 3: Causal ML and measurement | Interactive slides | Print slides (pdf) |
| R code: Quarto HTML | Python code: Jupyter Quarto HTML | ||
 |
Session 4: Traditional NLP and Linguistics | Interactive slides | Print slides (pdf) |
| R code: Quarto HTML | Python code: Jupyter Quarto HTML | ||
 |
Session 5: Embeddings | Interactive slides | Print slides (pdf) |
| R code: Quarto HTML | Python code: Jupyter Quarto HTML | ||
| Implementing word2vec in Colab | |||
 |
Session 6: Topic modeling | Interactive slides | Print slides (pdf) |
| Python code for LDA: Jupyter Quarto HTML | R code for STM and ETM: Quarto HTML |