modAL VS active_learning

Compare modAL vs active_learning 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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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. (by zeyademam)
active-learning distributed-data-parallel pytorch-implementation
Source Code
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modAL active_learning
4 1
2,140 52
1.5% -
1.9 1.8
2 months ago over 2 years ago
Python Python
MIT License MIT 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.

active_learning

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

What are some alternatives?

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

GPflowOpt - Bayesian Optimization using GPflow

diffgram - The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.

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.

adaptive - :chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

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 GPflowOpt active_learning vs diffgram modAL vs paramonte active_learning vs lightly modAL vs lightly active_learning vs adaptive modAL vs pretty-print-confusion-matrix modAL vs baybe modAL vs DataProfiler modAL vs Encord Active modAL vs DIgging modAL vs deep-active-learning