featuretools
Hyperactive
| featuretools | Hyperactive | |
|---|---|---|
| 2 | 8 | |
| 7,022 | 490 | |
| 0.3% | - | |
| 8.3 | 7.7 | |
| 19 days ago | 5 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" 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.
featuretools
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
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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...
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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?
functime - Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
mango - Parallel Hyperparameter Tuning in Python
Machine-Learning-with-Python - Small scale machine learning projects to understand the core concepts . Give a Star 🌟If it helps you. BONUS: Interview Bank coming up..!
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints
autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data [Moved to: https://github.com/autogluon/autogluon]
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
hyperimpute - A framework for prototyping and benchmarking imputation methods
OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
sapientml - Generative AutoML for Tabular Data
optuna-examples - Examples for https://github.com/optuna/optuna
upgini - Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs
optimization-tutorial - Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.