Machine Learning for Social Science, FallĀ 2021

Machine Learning for Social Science, Fall 2021

Resources
Outline:Book office hours:

Class files
i1 Session 1: Workflow and ML regression Interactive slides Print slides (pdf)
    R code Python code (View online)
i2 Session 2: Classification Interactive slides Print slides (pdf)
    R code Python code (View online)
i3 Session 3: Ensembling and Clustering Interactive slides Print slides (pdf)
    Example R code for clustering Python code (View online)
i4 Session 4: Basic NLP and Sentiment Interactive slides Print slides (pdf)
    Example R code for clustering Python code (View online)
i5 Session 5: Linguistics Interactive slides Print slides (pdf)
    No R code for this session Python code (View online)
i6 Session 6: Embedding Methods and Topic Modeling Interactive slides Print slides (pdf)
    R code Python code (View online)
i7 Session 7: Individual traits from text Interactive slides Print slides (pdf)
    Personality recognizer Twitter Emotion Recognition (Try online)
i8 Session 8: Causal Machine Learning Interactive slides Print slides (pdf)
    Python code (View online)  
i9 Session 9: ML for Policy Prediction Interactive slides Print slides (pdf)
i10 Session 10: Bias Interactive slides Print slides (pdf)
    Python code (View online) Example R code for SHAP
i11 Session 11: Neural Networks and Transfer Learning Interactive slides Print slides (pdf)
    Python code (View online) Example R code for Tensorflow/Keras
    FinBERT using pytorch FinBERT using huggingface transformers
    FinBERT using pytorch for fine-tuning  
i12 Session 12: Neural Networks for Image Classification Interactive slides Print slides (pdf)
    Python code (View online) Example R code for Tensorflow/Keras
    Detecting people in images