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AutoViML /AutoViz

Star1.9k

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

visualization python machine-learning scikit-learn python3 xgboost tableau automl tpot automated-machine-learning auto-sklearn automl-algorithms

UpdatedJun 10, 2024
Python

AutoViML /Auto_TS

Star764

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.

python time-series sklearn python3 arima prophet automl tpot time-series-analysis auto-sklearn autosklearn autokeras auto-arima auto-timeseries

UpdatedAug 20, 2024
Jupyter Notebook

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…

machine-learning binary-classification auto-sklearn

UpdatedOct 30, 2019
Python

uselessskills /auto_ml

Star13

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

python time-series forecasting pyramid auto-sklearn facebook-prophet

UpdatedAug 2, 2018
Jupyter Notebook

zuliani99 /AutoML-Benchmark

Star8

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

python benchmark machine-learning deep-learning kaggle dataset dash openml tpot auto-sklearn ploty mljar h2o-automl autogluon

UpdatedMay 16, 2025
Python

mecyc /TFG_RADAR_60GHZ

Star7

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.

python raspberry-pi machine-learning svm radar sensor randomforest k-nearest-neighbours k-nn aprendizaje-automatico auto-sklearn reconocimiento acconeer clasificador tabpfn radarwave

UpdatedJan 19, 2023
Jupyter Notebook

bhattbhavesh91 /auto-sklearn-tutorial

Sponsor

Star6

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

python data-science machine-learning tutorial automl auto-ml auto-sklearn

UpdatedMay 29, 2021
Jupyter Notebook

DunnBC22 /Python_Projects_with_Structured_data

Star5

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

sklearn exploratory-data-analysis keras structured-data binary-classification multiclass-classification auto-sklearn regression-analysis exploratory-data-visualizations sklearn-pipeline

UpdatedJul 14, 2023
Jupyter Notebook

nisarg14 /CSE523-Machine-Learning-Gophers

Star4

Warehouse Storage Optimization

machine-learning auto-ml auto-sklearn h20automl

UpdatedApr 11, 2021
Jupyter Notebook

CoDS-GCS /kgpip-public

Star4

KGpip - A Scalable AutoML Approach Based on Graph Neural Networks

scalability automl auto-sklearn graph-neural-networks

UpdatedNov 24, 2024
Python

qetdr /xAutoML-Project2

Star4

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

hyperparameter-optimization tpot auto-sklearn explainable-ml tpot-automl

UpdatedJan 16, 2023
Jupyter Notebook

ashish-kamboj /automl

Star1

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

tpot auto-sklearn mljar h2o-automl transmogrifai auto-viml autogluon pycaret evalml hyperopt-sklearn auto-keras lightautoml flaml

UpdatedJul 12, 2022
Python

AdamPaternostro /Azure-Databricks-auto-sklearn

Star1

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

data-science azure auto-sklearn azure-databricks

UpdatedJan 18, 2019
Shell

tejakiransirivella /Classical-AutoML

Star0

An AutoML framework for classical machine learning algorithms, automating model selection and hyperparameter tuning through Bayesian optimization, portfolio-based meta-learning, and multi-fidelity evaluation using Successive Halving.

benchmarking scikit-learn parallel-computing ray bayesian-optimization openml hyperparameter-tuning automl smac auto-sklearn meta-learning classical-machine-learning successive-halving