modAL-python / modALLinks
A modular active learning framework for Python
☆2,315Updated last year
Alternatives and similar repositories for modAL
Users that are interested in modAL are comparing it to the libraries listed below
Sorting:
- ☆1,165Updated 2 years ago
- PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book☆976Updated 2 years ago
- ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze t…☆885Updated 2 months ago
- Bayesian active learning library for research and industrial usecases.☆908Updated last week
- Deep Active Learning☆839Updated 3 years ago
- Model interpretability and understanding for PyTorch☆5,427Updated 2 weeks ago
- Pool-based active learning in Python☆787Updated 5 months ago
- A scikit-learn based module for multi-label et. al. classification☆951Updated last year
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆2,772Updated 5 months ago
- Algorithms for explaining machine learning models☆2,564Updated last week
- Automatic architecture search and hyperparameter optimization for PyTorch☆2,494Updated last year
- Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization☆1,936Updated 7 months ago
- python partial dependence plot toolbox☆861Updated last year
- A scikit-learn compatible neural network library that wraps PyTorch☆6,121Updated 2 months ago
- Algorithms for outlier, adversarial and drift detection☆2,439Updated this week
- ☆916Updated 2 years ago
- XAI - An eXplainability toolbox for machine learning☆1,202Updated 3 years ago
- Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.☆4,337Updated last month
- scikit-learn cross validators for iterative stratification of multilabel data☆879Updated last year
- A simple way to calibrate your neural network.☆1,162Updated 2 months ago
- Code for "High-Precision Model-Agnostic Explanations" paper☆807Updated 3 years ago
- Interpretability and explainability of data and machine learning models☆1,742Updated 7 months ago
- A standard framework for modelling Deep Learning Models for tabular data☆1,585Updated this week
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,537Updated 4 months ago
- Toolbox of models, callbacks, and datasets for AI/ML researchers.☆1,741Updated last week
- A curated list of awesome Active Learning☆781Updated 11 months ago
- Interpretability Methods for tf.keras models with Tensorflow 2.x☆1,035Updated last year
- Multi-class confusion matrix library in Python☆1,489Updated this week
- A library of sklearn compatible categorical variable encoders☆2,465Updated 4 months ago
- Hyper-parameter optimization for sklearn☆1,645Updated 6 months ago