deep-active-learning VS modAL

Compare deep-active-learning vs modAL and see what are their differences.

deep-active-learning

Deep Active Learning (by ej0cl6)
active-learning deep-active-learning
Source Code
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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 modAL
1 4
758 2,146
- 0.9%
10.0 1.9
over 1 year ago 3 months 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.

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.

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.

What are some alternatives?

When comparing deep-active-learning and modAL you can also consider the following projects:

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

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.

examples - Notebooks demonstrating example applications of the cleanlab library

GPflowOpt - Bayesian Optimization using GPflow

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

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

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

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

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

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

baybe - Bayesian Optimization and Design of Experiments

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