automl-pipeline

There are 29 repositories under automl-pipeline topic.

  • upgini/upgini

    Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

    Language:Python3305125

  • UrbsLab/STREAMLINE

    Simple Transparent End-To-End Automated Machine Learning Pipeline for Supervised Learning in Tabular Binary Classification Data

    Language:Jupyter Notebook786410

  • PKU-DAIR/mindware

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

    Language:Python59309

  • TsLu1s/atlantic

    Atlantic: Automated Data Preprocessing Framework for Machine Learning

    Language:Python29104

  • TsLu1s/tsforecasting

    TSForecasting: Automated Time Series Forecasting Framework

    Language:Python28101

  • david-thrower/cerebros-core-algorithm-alpha

    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.

    Language:Jupyter Notebook2751043

  • IBM/sail

    Library for streaming data and incremental learning algorithms.

    Language:Python2341612

  • Niklauseik/FiLM-Benchmark

    Benchmark pipeline for evaluating language models on financial tasks, including sentiment analysis and credit scoring. Supports over ten tasks with modular design for easy integration of new tasks. Provides automated performance metrics for standardized evaluation, benefiting researchers and practitioners in finance.

    Language:Python11101

  • jianzhnie/AutoTimm

    Auto torch image models: train and evaluation

    Language:Python8203

  • thompson0012/PyEmits

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

    Language:Python7211

  • CleverInsight/predicteasy

    Powerful AutoML toolkit

    Language:Jupyter Notebook40132

  • g0bel1n/TinyAutoML

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

    Language:Python4120

  • rdattafl/SNP-Data-Analysis-Project

    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)

    Language:Jupyter Notebook3100

  • dinaabdulrasoul/Bank-Marketing-Campaigns-ML-Models

    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.

    Language:Jupyter Notebook2100

  • dzaridis/simplatab-machine-learning-automator

    Simplatab: An Automated & Explainable Machine Learning Framework

    Language:Python2

  • EugenHotaj/daas

    AutoML as a Service

    Language:Python2201

  • eurobios-mews-labs/palma

    This library aims at providing tools for an automatic machine learning approach. As many tools already exist to establish one or the other component of an AutoML approach, the idea of this library is to provide a structure rather than to implement a complete service.

    Language:Python2195

  • ongaunjie1/pycaret_automl_streamlit

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

    Language:Jupyter Notebook2100

  • zgornel/Kdautoml.jl

    Knowledge-driven AutoML

    Language:Julia2200

  • blurred-machine/shrinkit

    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.

    Language:Python1100

  • Eva-Kaushik/AutoML

    AutoML

    Language:Python1100

  • fernandonieuwveldt/mlxops-pipeline

    Automating the ML Training Lifecycle with MLxOPS

    Language:Python1100

  • SaintAngeLs/CS-MINI-2024Z-AutoML_project_1

    Analyze the tunability of machine learning models with Grid Search, Random Search, and Bayesian Optimization. This project explores hyperparameter tuning methods on diverse datasets, comparing efficiency, stability, and performance. Featuring Random Forest, XGBoost, Elastic Net, and Gradient Boosting.

    Language:Python119

  • sannlin9/Projeto-Credit-Score

    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.

    Language:Jupyter Notebook1100

  • selmantabet/mjolnir-automl

    Project Mjölnir: An Automated Brute-Force Dataset-Model Combinatorics Training and Evaluation Pipeline for Computer Vision

    Language:Jupyter Notebook110

  • vxyagr/pintar.ai-automl

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

    Language:JavaScript1100

  • Ankurac7/AutoML

    Automated ML pipeline

    Language:Jupyter Notebook0100

  • chollette/Azure-Machine-Learning-Bank-Marketing-Classification

    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 provided for you.

    Language:Jupyter Notebook0101

  • SamoraHunter/ml_binary_classification_gridsearch_hyperOpt

    Automated machine learning. Evaluate a battery of binary classification algorithms across feature and hyper-parameter spaces.

    Language:Python0100