mlops-v2
clearml
mlops-v2 | clearml | |
---|---|---|
3 | 20 | |
451 | 5,269 | |
3.5% | 1.9% | |
3.7 | 7.7 | |
16 days ago | 4 days ago | |
Shell | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mlops-v2
- MLOps: Machine learning model management - Azure Machine Learning | Microsoft Learn
- Need help with Execute Python Script module in Azure ML Designer
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Create a Managed ML Inference Endpoint and deployment using Terraform
I would create a second step or stage for deploying the endpoint. There is no benefit to try and force terraform to do something it wasn't designed for. You can run AZ CLI commands from terraform, but I don't have experience doing so. Check out this mlops accelerator - https://github.com/Azure/mlops-v2 You can see how they use multiple pipeline for setting up the infrastructure then training and deploying the model.
clearml
- FLaNK Stack Weekly 12 February 2024
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clearml VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
- Is there any workflow orchestrator that is Hydra friendly ?
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Show HN: Open-source infra for data scientists
It looks like Magniv is targeting Python in general. This is similar to ClearML. What are the differentiating points to Magniv compared to similar products?
It seems like the product also integrates with SCM systems. Are you using gitea and then containers to push code and data to execution like CodeOcean?
https://github.com/allegroai/clearml
https://codeocean.com/
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[D] Drop your best open source Deep learning related Project
Hi there. ClearML is our open-source solution which is part of the PyTorch ecosystem. We would really appreciate it if you read our README and starred us if you like what you see!
- Start with powerful experiment management and scale into full MLOps with only 2 lines of code.
- Everything you need to log, share, and version experiments, orchestrate pipelines, and scale within one open-source MLOps solution.
- Start with powerful experiment management and scale into full MLOps with only 2 lines of code
What are some alternatives?
Time-Series-Library - A Library for Advanced Deep Time Series Models.
MLflow - Open source platform for the machine learning lifecycle
Data-Engineering-Roadmap - Roadmap for Data Engineering
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
MachineLearningNotebooks - Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
azure - Azure-related repository
kedro-great - The easiest way to integrate Kedro and Great Expectations
SynapseML - Simple and Distributed Machine Learning
streamlit - Streamlit — A faster way to build and share data apps.
computervision-recipes - Best Practices, code samples, and documentation for Computer Vision.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️