modAL VS Hyperactive

Compare modAL vs Hyperactive 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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Hyperactive

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. (by SimonBlanke)
hyperparameter-optimization scikit-learn Machine Learning Python Data Science parameter-tuning Xgboost Keras Deep Learning bayesian-optimization parallel-computing neural-architecture-search automated-machine-learning Optimization Pytorch feature-engineering hyperactive model-selection
Source Code
simonblanke.github.io
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modAL Hyperactive
4 8
2,143 490
0.8% -
1.9 7.7
2 months ago 5 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.

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.

Hyperactive

Posts with mentions or reviews of Hyperactive. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-12.

What are some alternatives?

When comparing modAL and Hyperactive 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.

mango - Parallel Hyperparameter Tuning in Python

GPflowOpt - Bayesian Optimization using GPflow

pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints

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

opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.

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

OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.

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

optuna-examples - Examples for https://github.com/optuna/optuna

baybe - Bayesian Optimization and Design of Experiments

optimization-tutorial - Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.

modAL vs active_learning Hyperactive vs mango modAL vs GPflowOpt Hyperactive vs pybobyqa modAL vs paramonte Hyperactive vs opytimizer modAL vs lightly Hyperactive vs OpenMetadata modAL vs pretty-print-confusion-matrix Hyperactive vs optuna-examples modAL vs baybe Hyperactive vs optimization-tutorial