Utilizes pycaret to automates machine learning workflows (Deployed at streamlit)

This is a Bank Marketing Machine Learning Classification Project in fulfillment of the Udacity Azure ML Nanodegree. In this project, you will learn to utilize Azure Machine Learning Studio and Azure Python SDK to create classifier models from scratch. The files and documentation with experiment instructions needed for replicating the project is …

Shrinkit is a powerful GUI-based Python library designed for automating machine learning tasks. With its intuitive interface, Shrinkit simplifies the process of building, training, and evaluating machine learning models, making it accessible to users of all skill levels. Shrinkit is a No-code package which can be used as a GUI.

Auto Machine learning platform as seen on https://www.youtube.com/watch?v=JHJLLiMnz6A

Automating the ML Training Lifecycle with MLxOPS

Projeto de criação de modelo de machine learning para score de credito, percorrendo todo o pipeline dos dados. Coleta, exploração, tratamento, limpeza, treino e deploy.

This project aims to create Machine Learning models using Azure's AutoML to find the best model that fits the data and Hypderdrive to find the best hyperparameters.

Knowledge-driven AutoML

AutoML as a Service.

A GitHub compiling the input data, Python and Jupyter Notebook scripts, and all relevant statistical outputs from running the AutoMLPipe-BC automated machine learning pipeline (from the Urbanowicz Lab - https://github.com/UrbsLab) on a large-scale single nucleotide polymorphism (SNP) dataset from patients with congenital heart disease (CHD)

Powerful AutoML toolkit

TinyAutoML is a comprehensive Pipeline Classifier Project thought as a Scikit-learn plugin

Sugar candy for data scientist. Easy manipulation in time-series data analytics works.

Auto torch image models: train and evaluation

Atlantic - Automated Data Preprocessing Framework for Supervised Machine Learning

Library for streaming data and incremental learning algorithms.

TSForecasting - Automated Time Series Forecasting Framework

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.

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