mleap
Pipeline deployer
Enables deployment of machine learning data pipelines and algorithms to production
MLeap: Deploy ML Pipelines to Production
2k stars
66 watching
313 forks
Language: Scala
last commit: 9 days ago
Linked from 2 awesome lists
data-pipelinespythonscalascikit-learnsparktensorflowtransformers
ethicalml/awesome-production-machine-learning
awesome-spark/awesome-sparkRelated projects:
| Repository | Description | Stars |
|---|---|---|
 aronchick/mlops-pipeline | Automates the end-to-end machine learning workflow from code commit to model deployment | 18 |
 paulescu/hands-on-train-and-deploy-ml | A step-by-step guide to building and deploying a Machine Learning-based REST API for predicting crypto prices using Python. | 758 |
 ebhy/budgetml | Simplifies deployment of machine learning models to production-ready endpoints with minimal configuration and cost. | 1,338 |
 oxid15/cascade | A lightweight MLOps library for small teams and individuals to manage machine learning model development lifecycle | 22 |
 minyus/pipelinex | A Python package to build and experiment with machine learning pipelines using Kedro, MLflow, and other tools | 224 |
 mop/bier | This project implements a deep metric learning framework using an adversarial auxiliary loss to improve robustness. | 39 |
 seldonio/tempo | An MLOps Python library that enables data scientists to deploy and orchestrate machine learning pipelines for production-ready inference. | 116 |
 lightforever/mlcomp | A distributed framework for building and managing complex machine learning pipelines with a user-friendly interface. | 188 |
 star-whale/starwhale | An MLOps platform providing tools and services for efficient machine learning development and deployment | 208 |
 sematic-ai/sematic | An open-source platform for building and managing machine learning pipelines with Python | 974 |
 mlrun/mlrun | A platform for managing and deploying machine learning workflows across the application lifecycle | 1,446 |
 runllm/aqueduct | An MLOps framework that allows developers to define and deploy machine learning workloads on any cloud infrastructure using a Python native API. | 521 |
 hydrospheredata/hydro-serving | A MLOps platform for deploying and versioning machine learning models in production. | 271 |
 omegaml/omegaml | An end-to-end MLOps platform that streamlines machine learning development, deployment, and collaboration. | 95 |
 valdanylchuk/swiftlearner | A collection of machine learning algorithms implemented in Scala for prototyping and experimentation. | 39 |