Fast and Accurate ML in 3 Lines of Code
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Updated
Jul 25, 2024 - Python
Fast and Accurate ML in 3 Lines of Code
Library for Semi-Automated Data Science
Fast and customizable framework for automatic ML model creation (AutoML)
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
Automated modeling and machine learning framework FEDOT
An open source python library for automated prediction engineering
An open source python library for automated feature engineering
Smart Process Analytics (SPA) is a software package for automatic machine learning. Given user-input data (and optional user preferences), SPA automatically cross-validates and tests ML and DL models. Model types are selected based on the properties of the data, minimizing the risk of data-specific variance.
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
Automated Machine Learning with scikit-learn
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Generative AutoML for Tabular Data
An open source python library for automated feature engineering based on Genetic Programming
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
MLimputer: Missing Data Imputation Framework for Supervised Machine Learning
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀
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