modAL
Hyperactive
| modAL | Hyperactive | |
|---|---|---|
| 4 | 8 | |
| 2,152 | 494 | |
| 0.6% | - | |
| 1.9 | 7.1 | |
| 3 months ago | 3 days ago | |
| Python | Python | |
| MIT License | MIT License |
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
-
modAL VS encord-active - a user suggested alternative
2 projects | 12 Apr 2023
- What are frameworks/tools used for Human-In-The-Loop (active) learning ?
-
Launch HN: Lightly (YC S21): Label only the data which improves your ML model
How does it differentiate from modAL?
https://github.com/modAL-python/modAL
- Active Learning Using Detectron2
Hyperactive
- Hyperactive Version 4.5 Released
- Hyperactive: An optimization and data collection toolbox for AutoML
- Hyperactive: Optimize computationally expensive models with powerful algorithms
- Show HN: Hyperactive – A highly versatile AutoML Toolbox
-
Hyperactive – Easy Neural Architecture Search for Deep Learning in Python
Check out the Neural Architecture Search Tutorial here: https://nbviewer.jupyter.org/github/SimonBlanke/hyperactive-...
Neural Architecture Search is just one of many optimization applications you can work on with Hyperactive. Check out the examples in the official github repository: https://github.com/SimonBlanke/Hyperactive/tree/master/examp...
-
Gradient-Free-Optimizers A collection of modern optimization methods in Python
Gradient-Free-Optimizers is a lightweight optimization package that serves as a backend for Hyperactive: https://github.com/SimonBlanke/Hyperactive
Hyperactive can do parallel computing with multiprocessing or joblib, or a custom wrapper-function.
What are some alternatives?
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 - OpenMetadata is a unified platform for discovery, observability, and governance powered by a central metadata repository, in-depth lineage, and seamless team collaboration.
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.