GalvanizeOpenSource / probabilistic-programming-intro
☆24Updated 7 years ago
Alternatives and similar repositories for probabilistic-programming-intro:
Users that are interested in probabilistic-programming-intro are comparing it to the libraries listed below
- Materials for talk on scikit-learn☆27Updated 9 years ago
- Python code for Hadley Whickham's article on Tidy Data.☆34Updated 8 years ago
- Tutorial on multilevel modeling, using Gelman radon example☆58Updated 9 years ago
- A collection of IPython Notebooks containing my research.☆20Updated 6 years ago
- Repository for the PyData DC 2016 tutorial☆29Updated 8 years ago
- My Jupyter notebook server☆19Updated 3 years ago
- repository for code related to the end-to-end data analysis in python workshop, from the Open Data Science Conference 2015☆15Updated 9 years ago
- Computational Statistics II Tutorial at SciPy 2015☆48Updated 9 years ago
- Code for Pythonic visualization blog post☆40Updated 8 years ago
- Repository for exploratory data transformation & visualization talk☆27Updated 8 years ago
- ☆26Updated 8 years ago
- Python solver for mixed-effects models☆97Updated 7 years ago
- ☆32Updated 7 years ago
- Tuning GBMs (hyperparameter tuning) and impact on out-of-sample predictions☆21Updated 7 years ago
- Notebook demonstrating use of LIME to interpret a model of long-term relationship success☆24Updated 7 years ago
- An in depth tutorial on sklearn's Pipeline and FeatureUnion classes.☆16Updated 8 years ago
- 2016 Election Data Hackathon, Bay Area WiMLDS☆18Updated 8 years ago
- Information Package☆44Updated 9 years ago
- Using data to dig into the 2015 NL Cy Young race☆10Updated 9 years ago
- ☆41Updated 9 years ago
- Materials for my PyData Seattle talk☆21Updated 9 years ago
- Files for Modern Statistical Workflow workshop☆10Updated 8 years ago
- Library for integrated use of H2O with Hyperopt☆13Updated last year
- ☆24Updated 6 years ago
- Materials for a workshop on developing undergraduate classes on Bayesian statistics.☆47Updated 8 years ago
- Tutorial in randomization inference, experimental design and analysis, and experiments in networks.