Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.

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

Product Categorization with Machine Learning

Computational experiments for the paper "A Comparison of AutoML Tools for Machine Learning, Deep Learning and XGBoost" (IJCNN 2021)

Diego: Data in, IntElliGence Out. A fast framework that supports the rapid construction of automated learning tasks. Simply create an automated learning study (Study) and generate correlated trials (Trial). Then run the code and get a machine learning model. Implemented using Scikit-learn API glossary, using Bayesian optimization and genetic algorithms for automated machine learning. Inspired by [Fast.ai](https://github.com/fastai/fastai).

Benchmark of current ML automation frameworks

Repositório com projetos utilizando ferramentas e bibliotecas para automatização de etapas de projetos de data science.

Tutorial on Auto_TS : Automatically build ARIMA, SARIMAX, VAR, FB Prophet and ML Models on Time Series data sets with a Single Line of Code

My Thesis: Auto-ML Tool for IoT Applications Version 1.0

This repo contains code file of all the AutoML libraries.

This repo contains analysis of Lending Club Credit rates and also case study for a client to get a fully funded loan at the lowest credit rate with a desired duration.

This repository includes sample code for AutoML tools AutoGluon, AutoKeras, AutoSklearn, H2O, PyCaret, TPOT

Awesome AutoML

Development of a credit scoring model

Predicting future winners of the Ingeborg-Bachmann-Preis with the help of NLP. Has a Flask app and a Rasa chatbot!

This repo's main purpose is to automate the ML process using scikit learn. I have performed the automation process in both classification and Regression

This project implements functions for building an ensemble of classifiers and regressors using the TPOT and auto-sklearn libraries with the help of a genetic algorithm evolved using the deap library.

Predicting Chronic Kidney Disease using AutoML (AutoSklearn) on Docker container