modAL VS DIgging

Compare modAL vs DIgging 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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DIgging

Decision Intelligence for digging best parameters in target environment. (by opendilab)
Searching bayesian-optimization evolutionary-algorithm reinforcement-learning
Source Code
opendilab.github.io
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modAL DIgging
4 1
2,140 81
1.5% -
1.9 10.0
2 months ago over 1 year ago
Python Python
MIT License Apache License 2.0
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.

DIgging

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

What are some alternatives?

When comparing modAL and DIgging 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.

tiny_gp - Tiny Genetic Programming in Python

GPflowOpt - Bayesian Optimization using GPflow

BayesianOptimization - A Python implementation of global optimization with gaussian processes.

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

auto-sklearn - Automated Machine Learning with scikit-learn

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

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

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

Gradient-Free-Optimizers - Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

baybe - Bayesian Optimization and Design of Experiments

vizier - Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

modAL vs active_learning DIgging vs tiny_gp modAL vs GPflowOpt DIgging vs BayesianOptimization modAL vs paramonte DIgging vs auto-sklearn modAL vs lightly DIgging vs nni modAL vs pretty-print-confusion-matrix DIgging vs Gradient-Free-Optimizers modAL vs baybe DIgging vs vizier