Workshops: Topic modeling in R
I recently conducted 2 workshops on Topic Modeling with the R STM package for 2 very different student populations:
The Berklee College of Music Digital Studies MBA in Valencia
Data Science at General Assembly
In the summer 2016, I had the pleasure of teaching a full Data Science Curriculum at General Assembly. Over 20 sessions and 60 hours, we covered a lot of ground, a lot of topics and some of the final students projects were amazing. The slides, code and datasets are all available on github at https://github.com/alexperrier/gads.
The course covers:
- Statistical inference
- Bias and variance, Learning curves and overfitting.
- Visualization with matplotlib and plotly
- Supervised: Regression and classification
- Unsupervised: Clustering
- Time series: ARMA models
- Tree based models: Random forests and Boosted trees
- Support Vector Machines
- NLP: sentiment analysis, Topic Modeling, POS tagging, wordnet, …
- Logistic regression
It was an intense curriculum!