mljar / mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
☆3,046Updated 3 weeks ago
Related projects ⓘ
Alternatives and complementary repositories for mljar-supervised
- Feature engineering package with sklearn like functionality☆1,913Updated this week
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.☆2,305Updated 3 months ago
- Predictive Power Score (PPS) in Python☆1,115Updated 8 months ago
- Algorithms for explaining machine learning models☆2,409Updated 3 months ago
- 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models☆2,736Updated last week
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆1,877Updated 3 months ago
- Extra blocks for scikit-learn pipelines.☆1,271Updated this week
- Algorithms for outlier, adversarial and drift detection☆2,240Updated last week
- Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Gra…☆1,725Updated 4 months ago
- Natural Gradient Boosting for Probabilistic Prediction☆1,654Updated last week
- EvalML is an AutoML library written in python.☆774Updated this week
- An open source python library for automated feature engineering☆7,257Updated this week
- A python library for decision tree visualization and model interpretation.☆2,957Updated 2 months ago
- Official implementation of the TabPFN paper (https://arxiv.org/abs/2207.01848) and the tabpfn package.☆1,217Updated 2 weeks ago
- A simple and efficient tool to parallelize Pandas operations on all available CPUs☆3,679Updated 4 months ago
- A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner