Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

Fast and customizable framework for automatic ML model creation (AutoML)

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

SensiML's open-source AutoML solution for Edge AI model development

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

Automatic Machine Learning Model Creation with GUI and Python.

Encodings for neural architecture search

The Cerebros package is an ultra-precise Neural Architecture Search (NAS) / AutoML that is intended to much more closely mimic biological neurons than conventional neural network architecture strategies.

Everything for the Paper: 'Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing'

An autoML for explainable text classification.

A SapientML plugin of SapientMLGenerator

a library to tune xgboost models

autoEnsemble : An AutoML Algorithm for Building Homogeneous and Heterogeneous Stacked Ensemble Models by Searching for Diverse Base-Learners

Awesome papers on AutoML (Automatic Machine Learning)

This repository contains an implementation of TPOT for obtaining optimal pipelines with the use of genetic algorithms.

Knowledge-driven AutoML

A lightweight, easy-to-use AutoML toolkit to help small businesses build, evaluate, and deploy practical machine learning models with minimal ML expertise. This repository provides end-to-end examples for data preparation, automated model selection, evaluation, and export for production.

A deep learning system that automatically designs optimal CNN architectures using Neural Architecture Search to classify lung - colon cancer from histopathology images. Achieves 99.72% accuracy across five cancer types with robust regularization. PyTorch-based solution ready for medical imaging deployment with exceptional generalization performane

Use your skills to help construct a sustainable society by predicting temperature in smart homes.