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Search results for pipeline mlops
mlops
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pipeline
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30 search results found
Jina
⭐
19,573
☁️ Build multimodal AI applications with cloud-native stack
Prefect
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14,603
Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines
Argo Workflows
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14,264
Workflow Engine for Kubernetes
Dagster
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9,467
An orchestration platform for the development, production, and observation of data assets.
Kedro
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9,353
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Great_expectations
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9,179
Always know what to expect from your data.
Taipy
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4,311
Turns Data and AI algorithms into production-ready web applications in no time.
Zenml
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3,626
ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
Polyaxon
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3,438
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
Pipelines
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3,368
Machine Learning Pipelines for Kubeflow
Ploomber
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3,318
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
Cube Studio
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1,710
cube studio开源云原生一站式机器学习/深度学习AI平台,支持sso登录,多租户/多项目组,数据资产对
Mlops
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1,427
MLOps examples
Mlrun
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1,177
Machine Learning automation and tracking
Sematic
⭐
913
An open-source ML pipeline development platform
Onepanel
⭐
704
The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
Neumai
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693
Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.
Bodywork Core
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358
ML pipeline orchestration and model deployments on Kubernetes, made really easy.
Gokart
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296
Gokart solves reproducibility, task dependencies, constraints of good code, and ease of use for Machine Learning Pipeline.
Whylogs Java
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179
Profile and monitor your ML data pipeline end-to-end
Zenbytes
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169
A simple guide to MLOps through ZenML and its various integrations.
Cicd Templates
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166
Manage your Databricks deployments and CI with code.
Kfp Tekton
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153
Kubeflow Pipelines on Tekton
Automlops
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92
Build MLOps Pipelines in Minutes
Inferoxy
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80
Service for quick deploying and using dockerized Computer Vision models
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.
Great_expectations_action
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68
A GitHub Action that makes it easy to use Great Expectations to validate your data pipelines in your CI workflows.
Examples
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60
📝 Examples of how to use Neptune for different use cases and with various MLOps tools
Krsh
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60
A declarative KubeFlow Management Tool
Kedro Kubeflow
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42
Kedro Plugin to support running workflows on Kubeflow Pipelines
Azure Machine Learning Mlops Workshop
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23
A workshop for doing MLOps on Azure Machine Learning
Bodywork Ml Pipeline Project
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21
Deployment template for a continuous training pipeline.
Pypely
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17
From local functions to cloud deployed pipelines
Aml Run
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17
GitHub Action that allows you to submit a run to your Azure Machine Learning Workspace.
Smartpipeline
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16
A framework for rapid development of robust data pipelines following a simple design pattern
Continuous Adaptation For Machine Learning System To Data Changes
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16
https://blog.tensorflow.org/2021/12/continuous-ada
Composable Logs
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16
Python library to run ML/data pipelines on stateless compute infrastructure (that may be ephemeral or serverless). Please see the documentation site with more details and demo:
Tfx Kubeflow Pipelines
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15
Kubeflow pipelines built on top of Tensorflow TFX library
Anomaly Detection Pipeline Kedro
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8
Anomaly Detection Pipeline with Isolation Forest model and Kedro framework
Bodywork Serve Model Project
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7
Deployment template for serving a ML model as web-service with a REST API.
Kubeflow Gke Docs
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7
Documentation for Kubeflow on Google Cloud
Bodywork Batch Job Project
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6
Deployment template for batch-scoring a dataset with a pre-trained ML model.
Kubernetes Operator Roiergasias
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5
'Roiergasias' kubernetes operator is meant to address a fundamental requirement of any data science / machine learning project running their pipelines on Kubernetes - which is to quickly provision a declarative data pipeline (on demand) for their various project needs using simple kubectl commands. Basically, implementing the concept of No Ops. The fundamental principle is to utilise best of docker, kubernetes and programming language features to run a workflow with minimal workflow definition s
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