ericmjl / distributions
Central repository for my distributions figures
☆16Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for distributions
- ☆37Updated 6 years ago
- Course in Probabilistic Programming in Python for the 2018 EU Summer School☆23Updated 6 years ago
- A collection of IPython Notebooks containing my research.☆20Updated 6 years ago
- HTTP interface to Stan, a package for Bayesian inference.☆40Updated 4 months ago
- ☆15Updated 6 years ago
- A `select` accessor for easier subsetting of pandas DataFrames and Series☆34Updated last year
- Implementation of simulation based calibration for PyMC and Bambi☆32Updated 2 months ago
- My Jupyter notebook server☆19Updated 2 years ago
- ☆32Updated 7 years ago
- Slides and materials for workshop on "Two views on regression with PyMC3 and scikit-learn"☆19Updated last year
- Conventionally parameterized probability distributions☆35Updated 2 months ago
- A command line utility to create kernels in Jupyter from virtual environments.☆16Updated 7 years ago
- ☆28Updated 7 years ago
- Python solver for mixed-effects models☆98Updated 6 years ago
- pybroom, the python's broom to tidy up messy fit results!☆14Updated 7 years ago
- Decorator for PyMC3☆50Updated 3 years ago
- An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".☆24Updated 5 months ago
- Repo for PyData 2019 Tutorial - New Trends in Estimation and Inference☆26Updated 5 years ago
- Data exploration library with a pandas-like API☆74Updated 4 years ago
- ☆15Updated 2 years ago
- A Bayesian testing framework written in Python.☆95Updated 9 years ago
- Probabilistic programming in Python workshop at Oslo universitetssykehus HF☆36Updated 8 years ago
- ☆30Updated 7 years ago
- WIP predicted survival functions☆37Updated 5 years ago
- ☆27Updated 5 years ago
- Python implementation of R package breakDown☆41Updated last year
- Materials for my talk at PyData Chicago 2016☆20Updated 7 years ago
- Tutorial on interpreting and understanding machine learning models☆68Updated 6 years ago