Alternatives and similar repositories for modAL

Users that are interested in modAL are comparing it to the libraries listed below

• google / active-learning
  ☆1,160Updated 2 years ago
• rmunro / pytorch_active_learning
  PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book
  ☆966Updated 2 years ago
• NUAA-AL / ALiPy
  ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze t…
  ☆883Updated 2 years ago
• baal-org / baal
  Bayesian active learning library for research and industrial usecases.
  ☆900Updated 3 weeks ago
• ej0cl6 / deep-active-learning
  Deep Active Learning
  ☆837Updated 2 years ago
• ntucllab / libact
  Pool-based active learning in Python
  ☆788Updated 2 months ago
• SeldonIO / alibi-detect
  Algorithms for outlier, adversarial and drift detection
  ☆2,405Updated last month
• scikit-multilearn / scikit-multilearn
  A scikit-learn based module for multi-label et. al. classification
  ☆940Updated last year
• SeldonIO / alibi
  Algorithms for explaining machine learning models
  ☆2,532Updated last month
• marcotcr / anchor
  Code for "High-Precision Model-Agnostic Explanations" paper
  ☆804Updated 2 years ago
• uncertainty-toolbox / uncertainty-toolbox
  Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
  ☆1,906Updated 4 months ago
• pytorch / captum
  Model interpretability and understanding for PyTorch
  ☆5,307Updated last week
• EthicalML / xai
  XAI - An eXplainability toolbox for machine learning
  ☆1,190Updated 3 years ago
• sicara / tf-explain
  Interpretability Methods for tf.keras models with Tensorflow 2.x
  ☆1,028Updated last year
• scikit-learn-contrib / metric-learn
  Metric learning algorithms in Python
  ☆1,424Updated 11 months ago
• IDSIA / sacred
  Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
  ☆4,315Updated 7 months ago
• TeamHG-Memex / eli5
  A library for debugging/inspecting machine learning classifiers and explaining their predictions
  ☆2,772Updated 2 months ago
• gpleiss / temperature_scaling
  A simple way to calibrate your neural network.
  ☆1,153Updated 3 years ago
• hyperopt / hyperopt-sklearn
  Hyper-parameter optimization for sklearn
  ☆1,635Updated 3 months ago
• salesforce / OmniXAI
  OmniXAI: A Library for eXplainable AI
  ☆935Updated 11 months ago
• interpretml / DiCE
  Generate Diverse Counterfactual Explanations for any machine learning model.
  ☆1,422Updated 2 weeks ago
• automl / Auto-PyTorch
  Automatic architecture search and hyperparameter optimization for PyTorch
  ☆2,456Updated last year
• google-research / uda
  Unsupervised Data Augmentation (UDA)
  ☆2,192Updated 3 years ago
• SauceCat / PDPbox
  python partial dependence plot toolbox
  ☆860Updated 10 months ago
• pavlin-policar / openTSNE
  Extensible, parallel implementations of t-SNE
  ☆1,543Updated last month
• autonomio / talos
  Hyperparameter Experiments with TensorFlow and Keras
  ☆1,638Updated last year
• stanfordmlgroup / ngboost
  Natural Gradient Boosting for Probabilistic Prediction
  ☆1,758Updated last month
• Trusted-AI / AIX360
  Interpretability and explainability of data and machine learning models
  ☆1,710Updated 4 months ago
• google / uncertainty-baselines
  High-quality implementations of standard and SOTA methods on a variety of tasks.
  ☆1,517Updated last month
• scikit-multiflow / scikit-multiflow
  A machine learning package for streaming data in Python. The other ancestor of River.
  ☆779Updated last year