alibi
Model explainer
A Python library for explaining machine learning models
Algorithms for explaining machine learning models
2k stars
58 watching
252 forks
Language: Python
last commit: 4 months ago
Linked from 4 awesome lists
counterfactualexplanationsinterpretabilitymachine-learningxai
ethicalml/awesome-production-machine-learning
kelvins/awesome-mlops
krzjoa/awesome-python-data-scienceRelated projects:
| Repository | Description | Stars |
|---|---|---|
 shap/shap | Provides an algorithm to explain the output of machine learning models using game theory and Shapley values. | 22,876 |
 keon/algorithms | A collection of Python implementations of various algorithms and data structures. | 24,076 |
 pycaret/pycaret | An automation tool for machine learning workflows in Python | 8,955 |
 clips/pattern | A comprehensive Python module for web mining and analysis of text data. | 8,750 |
 meta-llama/codellama | Provides inference code and tools for fine-tuning large language models, specifically designed for code generation tasks | 16,039 |
 trekhleb/homemade-machine-learning | Practices implementing popular machine learning algorithms from scratch to gain a deeper understanding of their mathematics | 23,121 |
 jphall663/interpretable_machine_learning_with_python | Teaching software developers how to build transparent and explainable machine learning models using Python | 673 |
 interpretml/interpret | An open-source package for explaining machine learning models and promoting transparency in AI decision-making | 6,296 |
 stability-ai/stability-sdk | An SDK for interacting with Stability AI's APIs to generate images and other artifacts through latent diffusion inference. | 2,425 |
 openvinotoolkit/anomalib | A deep learning library for detecting anomalies in data with algorithms and tools for benchmarking, training, and deploying models. | 3,813 |
| interpretml/dice | Provides counterfactual explanations for machine learning models to facilitate interpretability and understanding. | 1,364 |
 sergioburdisso/pyss3 | A Python package implementing an interpretable machine learning model for text classification with visualization tools | 336 |
 pgmpy/pgmpy | A Python package for working with Bayesian Networks and related models. | 2,748 |
 h2oai/mli-resources | Provides tools and techniques for interpreting machine learning models | 484 |
 blobcity/autoai | A Python-based framework for automating the process of finding and training the best-performing machine learning model for regression and classification tasks on numerical data. | 174 |