modAL VS pybads

Compare modAL vs pybads and see what are their differences.

modAL

A modular active learning framework for Python (by modAL-python)
scikit-learn Machine Learning Python active-learning machine-learning-library machine-learning-algorithms machine-learning-api active-learning-module bayesian-optimization
Source Code
modal-python.github.io
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pybads

PyBADS: Bayesian Adaptive Direct Search optimization algorithm for model fitting in Python (by acerbilab)
bayesian-optimization log-likelihood noiseless-functions noisy-functions optimization-algorithms Python
Source Code
acerbilab.github.io
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modAL pybads
4 1
2,140 58
1.5% -
1.9 4.7
2 months ago about 2 months ago
Python Python
MIT License BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

modAL

Posts with mentions or reviews of modAL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-12.

pybads

Posts with mentions or reviews of pybads. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing modAL and pybads you can also consider the following projects:

active_learning - Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training with torch's DDP.

emukit - A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

GPflowOpt - Bayesian Optimization using GPflow

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

paramonte - ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.

lightly - A python library for self-supervised learning on images.

pretty-print-confusion-matrix - Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

baybe - Bayesian Optimization and Design of Experiments

DataProfiler - What's in your data? Extract schema, statistics and entities from datasets

Encord Active - Open source active learning toolkit to find failure modes in your computer vision models, prioritize data to label next, and drive data curation to improve model performance.

DIgging - Decision Intelligence for digging best parameters in target environment.

deep-active-learning - Deep Active Learning

modAL vs active_learning pybads vs emukit modAL vs GPflowOpt pybads vs nni modAL vs paramonte modAL vs lightly modAL vs pretty-print-confusion-matrix modAL vs baybe modAL vs DataProfiler modAL vs Encord Active modAL vs DIgging modAL vs deep-active-learning