Hyperactive
Auto_ViML
| Hyperactive | Auto_ViML | |
|---|---|---|
| 8 | 2 | |
| 490 | 490 | |
| - | - | |
| 7.7 | 4.2 | |
| 5 months ago | 5 months ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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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.
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.
Auto_ViML
- library / framework to test multiple sklearn regression models at once
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AutoNLP for Automating Twitter Sentiment Analysis
To install this we can use a simple pip command. Since AutoNLP belongs to autoviml we need to install that.
What are some alternatives?
mango - Parallel Hyperparameter Tuning in Python
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints
AutoViz - Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
Python-Schema-Matching - A python tool using XGboost and sentence-transformers to perform schema matching task on tables.
OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
evalml - EvalML is an AutoML library written in python.
optuna-examples - Examples for https://github.com/optuna/optuna
sapientml - Generative AutoML for Tabular Data
optimization-tutorial - Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.
Auto_TS - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.