Automated Car with Reinforcement Learning. Learning is done using penalty and rewards.

Automated ML pipeline for Iris dataset classification using Decision Tree. Features PCA dimensionality reduction and standard scaling.

An improved version of Turbo algorithm for the Black-box optimization competition organized by NeurIPS 2020

ArcFace head module for Automated feature extraction/Deep Metric Learning with Autokeras

Automorphic Equivalence-aware Graph Neural Network. NeurIPS 2021.

A collection of Python coded analysis and automation of risk mitigation strategies in portfolio management.

Next generation framework for collaborative data science and automated machine learning

Classify imgur posts

RADSSo tool in python 3.5

Open source library intended to bridge the gap between a non-technical audience and the ability to engineer Intelligent solutions.

# kaefa kwangwoon automated exploratory factor analysis for improving research capability to identify unexplained factor structure with complexly cross-classified multilevel structured data in R environment

Automated machine learning and data mining software

This web application is useful for scratch analysis

Automate data analysis and modeling, so you can focus on the work that makes an impact. If you care about efficiency and data security like us, then this is the AutoML tool you are looking for.

Meta-Padawan solution to the NeurIPS (2021) - Few-shot learning competition.

This project predicts whether a person is at the risk of having a heart attack or not by using Automated Machine Learning Techniques

Repository for Reproducibility for the Paper: "Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML"

Neste projeto de Análise de Recursos Humanos, temos como objetivo responder questões-chave sobre gestão de talentos e rotatividade de colaboradores em uma empresa fictícia.

Fully automated machine learning using LLMs.

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.