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mlops
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16 search results found
Seldon Core
⭐
4,078
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Budgetml
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1,290
Deploy a ML inference service on a budget in less than 10 lines of code.
Hands On Train And Deploy Ml
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408
Train and Deploy an ML REST API to predict crypto prices, in 10 steps
Kedro Mlflow
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175
A kedro-plugin for integration of mlflow capabilities inside kedro projects (especially machine learning model versioning and packaging)
Cicd Templates
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166
Manage your Databricks deployments and CI with code.
Omegaml
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93
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
Monai Deploy App Sdk
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74
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.
Mlops.net
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69
A machine learning model operations and management tool for ML.NET
Mljet
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66
Minimalistic ML-models auto deployment tool
Serving Machine Learning Models
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33
This repository contains instructions, template source code and examples on how to serve/deploy machine learning models using various frameworks and applications such as Docker, Flask, FastAPI, BentoML, Streamlit, MLflow and even code on how to deploy your machine learning model as an android app.
Aml Deploy
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28
GitHub Action that allows you to deploy machine learning models in Azure Machine Learning.
Racetrack
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27
An opinionated framework for deploying, managing, and serving application workloads
Sdk Python
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23
Python library for Modzy Machine Learning Operations (MLOps) Platform
Full Stack On Prem Cv Mlops
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23
1 config, 1 command from Jupyter Notebook to serve Millions of users
Mldevops
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20
ML DevOps using GitHub Actions and Azure Machine Learning
Great Ai
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7
Transform your prototype AI code into production-ready software.
Inferex
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6
Inferex looks after serving, scaling, securing & monitoring your models, and liberating your ML team from the overhead of managing and maintaining infrastructure.
Machinealgobox
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6
Explore common ML algorithms, from scratch implementations to real-world use cases, Each algorithm is accompanied by clear explanations, code implementations, and real-world use cases, enabling you to grasp their underlying principles and apply them to different problem domains.
Bodywork Scikit Fastapi Project
⭐
5
Deploy Scikit-Learn models on Kubernetes, using FastAPI with Bodywork.
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