Fast and Accurate ML in 3 Lines of Code
-
Updated
May 28, 2024 - Python
Fast and Accurate ML in 3 Lines of Code
An open source python library for automated feature engineering
Automated modeling and machine learning framework FEDOT
This automated anomaly detection preprocessing pipeline can be used to automatically preprocess tabular data for anomaly detection methods.
A collection of Python coded analysis and automation of risk mitigation strategies in portfolio management.
MLimputer - Missing Data Imputation Framework for Supervised Machine Learning
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
An open source python library for automated prediction engineering
Fast and customizable framework for automatic ML model creation (AutoML)
An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀
R package for automation of machine learning, forecasting, model evaluation, and model interpretation
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Low code machine learning library, specified for insurance tasks: prepare data, build model, implement into production.
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Generative AutoML for Tabular Data
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
Library for Semi-Automated Data Science
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
Add a description, image, and links to the automated-machine-learning topic page so that developers can more easily learn about it.
To associate your repository with the automated-machine-learning topic, visit your repo's landing page and select "manage topics."