modAL VS deep-active-learning

Compare modAL vs deep-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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deep-active-learning

Deep Active Learning (by ej0cl6)
active-learning deep-active-learning
Source Code
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modAL deep-active-learning
4 1
2,140 758
1.5% -
1.9 10.0
2 months ago over 1 year 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.

deep-active-learning

Posts with mentions or reviews of deep-active-learning. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-16.

What are some alternatives?

When comparing modAL and deep-active-learning 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.

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

GPflowOpt - Bayesian Optimization using GPflow

examples - Notebooks demonstrating example applications of the cleanlab library

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

argilla - Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.

awesome-active-learning - A curated list of awesome Active Learning

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

cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

baybe - Bayesian Optimization and Design of Experiments

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

modAL vs active_learning deep-active-learning vs lightly modAL vs GPflowOpt deep-active-learning vs examples modAL vs paramonte deep-active-learning vs argilla modAL vs lightly deep-active-learning vs awesome-active-learning modAL vs pretty-print-confusion-matrix deep-active-learning vs cleanlab modAL vs baybe deep-active-learning vs adaptive