ml-pipeline
There are 99 repositories under ml-pipeline topic.
sematic-ai/sematic
An open-source ML pipeline development platform
alexjc/weboptout
Opt-Out tool to check Copyright reservations in a way that even machines can understand.
data-mining-in-action/DMIA_ProductionML_2021_Spring
Репозиторий направления Production ML, весна 2021
hifxit/dataligo
A library to accelerate ML and ETL pipeline by connecting all data sources
Vevesta/VevestaX
2 Lines of code to track ML experiments + EDA + check into Github
rahul765/Machine-Learning-Pipelines
From data gathering to model deployment. Complete ML pipeline using Docker, Airflow and Python.
ziss11/heart-failure-detection
Dicoding Submission MLOps Heart Failure Detection using ML Pipeline, Heroku Deployment and Prometheus Monitoring
otaviog/rflow
RFlow - A workflow framework for agile machine learning
awesome-mlops/awesome-ml-pipelines
A curated list of awesome open source tools and commercial products that will help you manage machine learning and data-science workflows and pipelines 🚀
awesome-mlops/awesome-mlops-kubernetes
A curated list of awesome open source tools and commercial products that will help you train, deploy, monitor, version, scale, and secure your production machine learning on kubernetes 🚀
dimikara/Optimizing-an-ML-Pipeline-in-Azure
Optimizing an ML Pipeline in Azure - A Machine Learning Engineer Project
ilias-chatzistefanidis/HetNets-steering
Repo containing Channel Quality Indicator (CQI) data from real car routes in Greece. It contains a reproducable notebook with the implementation of a Bidirectional LSTM Neural Network for real-time CQI forecasting in heterogeneous ultra-dense beyond-5G networks.
zamaniali1995/ml-pipeline
Our goal with this ML pipeline template is to create a user friendly utility to drastically speed up the development and implementation of a machine learning model for all sorts of various problems.
bodywork-ml/bodywork-pipeline-utils
A package of utilities for engineering ML pipelines.
piyush-singhal/airflow-docker
Install Airflow using docker
ArslanKAS/ML_pipeline
Machine Learning Project Pipeline
dieterich-lab/ASyH
The Anonymous Synthesizer for Health Data
Fatiima-Ezzahra/Operationalizing-Machine-Learning-in-Azure
This project is part of the Udacity Azure ML Nanodegree. In this project, we use Azure to configure a cloud-based machine learning production model, deploy it, and consume it. We also create, publish, and consume a pipeline.
gershonc/mlflow_showcase
Showcase of MLflow capabilities
nshutijean/DVC-Mlflow-pipeline
📅 A demo about versioning data and tracking ML experiments using DVC and Mlflow respectively.
aravind-selvam/ml-pipeline-using-stroke-data
This project demonstrates the implementation of a ML pipeline and CI/CD using data on heart strokes. The pipeline includes data preprocessing, model training and evaluation, and deployment. The project leverages GitHub for version control and integration with GitHub actions for efficient and automated model updates.
ashish-kamboj/mlops
Repository contains the detail about ML model deployment and building end-to-end ML pipeline for production
chris-chris/xmodel
Multi Cloud Model Management System for Machine Learning
jasmeetsb/airflow_ml_ops
Sample Airflow ML Pipelines
Kusainov/udacity-disaster-response
Disaster response project containing web app, ETL, ML pipelines
MaxWolf-01/sklearn-svm-classification-pipeline-api
A flask api for text-classification with sklearn pipelines.
sadiaTab/Disaster_Response_Pipeline
This project, in collaboration with Figure Eight as part of Udacity's Data Science Nanodegree program, focuses on real-time message categorization for disaster events. It involves an ETL pipeline, ML pipeline, and Web app for classifying disaster response messages.
vasnake/spark.ml.SpatialJoinTransformer
spark.ml.transformer that join input dataset with external data using Spatial Join
yennanliu/HousePricePredAPI
ML api predict house price wrapped in Docker and deployed to AWS ECS/Fargate | #DE |#ML
ziss11/fake-news-classification
Dicoding Submission MLOps Fake News Classification using ML Pipeline
mazba-ahamad/Generating-Composite-Proxy-Target-Variable-for-Machine-Learning-Models-of-Business-Decisions
A multi-criteria decision analysis (MCDA)-based composite proxy target variable generation technique for business decision modeling that uses relevant features or independent variables conceptually related to the intended target variable.
mesudepolat/ml-pipeline
Creating an end-to-end machine learning pipeline, implementing experiment tracking with MLflow, and performing hyperparameter optimization using Optuna.
Neel7317/MLOPs_with_kedro
simple MLOPs demo with kedro..
NoahRuhmer/AMLS-Star-Galaxy-Classification
This project is a full machine learning pipeline for Star/Galaxy classification using the SDSS dataset. It also contains a detailed report on the development and a DockerFile to easily replicate the results.