jameslamb / lightgbm-dask-testing
Test LightGBM's Dask integration on different cluster types
☆12Updated 2 weeks ago
Related projects: ⓘ
- ☆15Updated 2 years ago
- ☆17Updated 2 years ago
- Comparing Polars to Pandas and a small introduction☆43Updated 3 years ago
- Website: Data Umbrella & PyMC open source sessions☆26Updated 3 months ago
- Introduction to scikit-learn: Machine Learning in Python☆20Updated 2 years ago
- A scikit-learn compatible estimator based on business-rules with interactive dashboard included☆28Updated 3 years ago
- "Actionable Ethics for Data Scientists" Workshop Material @ ODSC☆10Updated 3 months ago
- Talks / presentations / tutorials about Fairlearn and fairness in ML☆23Updated 2 years ago
- Advanced Python for Data Science Workshop☆13Updated last month
- A library for Time-Series exploration, analysis & modelling.☆17Updated 3 years ago
- A practical, explainable and effective method for reducing bias in machine learning algorithms.☆21Updated 4 years ago
- Tutorial covering a new workflow available going from pandas to scikit-learn☆40Updated last year
- Structural Time Series on US electricity demand data☆23Updated 3 years ago
- ☆15Updated last year
- Public code & notebooks accompanying our blog posts & YouTube tutorials (https://www.youtube.com/c/PyMCLabs)☆23Updated 4 months ago
- Explorations of survival analysis in Python☆50Updated last year
- ☆13Updated last year
- Python package for Bayesian & Frequentist A/B Testing☆11Updated last year
- A `select` accessor for easier subsetting of pandas DataFrames and Series☆33Updated last year
- ☆19Updated 3 years ago
- this repo might get accepted☆29Updated 3 years ago
- Function for automatically detecting Simpson's Paradox☆18Updated 3 years ago
- Tutorial for PyData London 2019 on AB Test by cluster☆14Updated 5 years ago
- Material for the PyLadies Bayesian Tutorial, Feb 11, 2020☆12Updated last year
- Project template for highly effective data science workflows☆29Updated 5 months ago
- Workshop on Target Leakage in Machine Learning I taught at ODSC Europe 2018 (London) and ODSC East 2019, 2020 (Boston)☆36Updated 4 years ago
- Supporting material for the book club☆14Updated 2 years ago
- A set of decks and notebooks with exercises for use in a hands-on causal inference tutorial session☆33Updated 2 years ago
- Demo on how to use Prefect with Docker☆26Updated 2 years ago
- Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.☆20Updated 2 years ago