bodywork-pipeline-with-aporia-monitoring VS VevestaX

Compare bodywork-pipeline-with-aporia-monitoring vs VevestaX and see what are their differences.

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bodywork-pipeline-with-aporia-monitoring VevestaX
1 10
4 27
- -
0.0 0.0
almost 2 years ago over 1 year ago
Jupyter Notebook Jupyter Notebook
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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bodywork-pipeline-with-aporia-monitoring

Posts with mentions or reviews of bodywork-pipeline-with-aporia-monitoring. We have used some of these posts to build our list of alternatives and similar projects.

VevestaX

Posts with mentions or reviews of VevestaX. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-12.

What are some alternatives?

When comparing bodywork-pipeline-with-aporia-monitoring and VevestaX you can also consider the following projects:

evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

MLOps - End to End toy example of MLOps

bodywork-pymc3-project - Serving Uncertainty with Bayesian inference, using PyMC3 with Bodywork

vertex-ai-samples - Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.

Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.

ml-pipeline-engineering - Best practices for engineering ML pipelines.

mlflow-deployments - Source code for the post Effortless deployments with MLFlow, showcasing how logging models using MLFLow can provide you want to easily deploy them in production later.

bodywork - ML pipeline orchestration and model deployments on Kubernetes.

OAD - Collection of tools and scripts useful to automate microscopy workflows in ZEN Blue using Python and Open Application Development tools and AI tools.

mlflow-easyauth - Deploy MLflow with HTTP basic authentication using Docker