valeman / Awesome_CatBoost
The repository to showcase the best framework for tabular data - the Awesome CatBoost
☆180Updated 2 months ago
Related projects ⓘ
Alternatives and complementary repositories for Awesome_CatBoost
- Practical Guide to Applied Conformal Prediction, published by Packt☆145Updated 9 months ago
- Forecasting: principles and practice in python☆89Updated last year
- ☆273Updated last year
- Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.☆193Updated 10 months ago
- Python implementation of binary and multi-class Venn-ABERS calibration☆134Updated 2 months ago
- 👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster☆86Updated last month
- The Orange Book of Machine Learning☆30Updated 3 months ago
- Python package for conformal prediction☆459Updated 2 months ago
- Quantile Regression Forests compatible with scikit-learn.☆210Updated this week
- ☆112Updated 9 months ago
- This projects contains different conformal methods and approaches. Includes code generated for a experimental evaluation of a multidimens…☆19Updated 7 months ago
- Compendium of free ML reading resources☆266Updated this week
- The best repository showing why SMOTE and resampling methods might not be the answer for imbalanced data problems☆30Updated last month
- Python library for Applied Computational Supply Chain & Logistics. Unlock Neural Nets, Bayesian EOQ, Optimization, Time Series, and more …☆60Updated this week
- ☆46Updated last month
- The best repository showing why transformers might not be the answer for time series forecasting and showcasing the best SOTA non transfo…☆537Updated 2 weeks ago
- Modern Time Series Forecasting with Python, published by Packt☆453Updated 6 months ago
- A lightweight and fast auto-ml library☆71Updated 3 weeks ago
- Repository for the explanation method Calibrated Explanations (CE)☆54Updated this week
- 👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.☆302Updated this week
- Tools to Transform a Time Series into Features and Target a.k.a Supervised Learning☆98Updated last year
- Extension of crepes package, to enable weighted conformal prediction and conformal predictive systems that can handle covariate shifts.☆21Updated 6 months ago
- Shapley Interactions for Machine Learning☆221Updated this week
- Examples of python neural net and ML stock prediction methods with sample stock data.☆269Updated 10 months ago
- ☆195Updated this week
- Forecasting: Principles and Practice☆30Updated 3 years ago
- Tries to shrink your Pandas column dtypes with no data loss so you have more spare RAM☆50Updated 10 months ago
- Modern Time Series Forecasting with Python 2E, Published by Packt☆52Updated last week
- Applied Data Science for Credit Risk☆82Updated this week