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

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.

autosklearn-zeroconf is a fully automated binary classifier. It is based on the AutoML challenge winner auto-sklearn. Give it a dataset with known outcomes (labels) and it returns a list of predicted outcomes for your new data. It even estimates the precision for you! The engine is tuning massively parallel ensemble of machine learning pipelines…

In this repository we test AutoML approaches for time-series forecasting

Benchmark for some usual automated machine learning, such as: AutoSklearn, MLJAR, H2O, TPOT and AutoGluon. All visualized via a Dash Web Application

TFG realizado en la Universidad de Burgos del desarrollo de una aplicación para el uso de un Radar de 60 GHz de la marca Acconeer.

Small tutorial on auto-sklearn which is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.

This repository includes projects using datasets of structured data (non-Spark). The projects use Python, NumPy, Pandas, Matplotlib, Seaborn, TensorFlow, Pytorch, and Sklearn.

Explainable Automated Machine Learning Framework for Predicting the Risk of Major Adverse Cardiac Event (MACE)

KGpip - A Scalable AutoML Approach Based on Graph Neural Networks

Warehouse Storage Optimization

AutoML Libraries for training multiple ML models in one go with less code.

Shows how to install auto-sklearn on an Azure Databricks cluster

A python package that computes LP on the entire sklearn space.

Find out whether a product is Sportswear or not based on URL texts using Machine Learning in Python