budgetml
MLflow
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| budgetml | MLflow | |
|---|---|---|
| 4 | 54 | |
| 1,332 | 17,234 | |
| 0.2% | 2.4% | |
| 0.0 | 9.9 | |
| 2 months ago | 2 days ago | |
| Python | Python | |
| Apache License 2.0 | 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.
budgetml
MLflow
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
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EL5: Difference between OpenLLM, LangChain, MLFlow
MLFlow - http://mlflow.org
- Explain me how websites like Dall-E, chatgpt, thispersondoesntexit process the user data so quickly
- [D] What licensed software do you use for machine learning experimentation tracking?
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Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
MLflow:
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Options for configuration of python libraries - Stack Overflow
In search for a tool that needs comparable configuration I looked into mlflow and found this. https://github.com/mlflow/mlflow/blob/master/mlflow/environment_variables.py There they define a class _EnvironmentVariable and create many objects out of it, for any variable they need. The get method of this class is in principle a decorated os.getenv. Maybe that is something I can take as orientation.
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[D] Is there a tool to keep track of my ML experiments?
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
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[Q] Is there a tool to keep track of my ML experiments?
Hi, you should have a look at ML flow https://mlflow.org or weight and biases https://wandb.ai/site
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Looking for recommendations to monitor / detect data drifts over time
Dumb question, how does this lib compare to other libs like MLFlow, https://mlflow.org/?
What are some alternatives?
pinferencia - Python + Inference - Model Deployment library in Python. Simplest model inference server ever.
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
ck - Collective Mind (CM) is a simple, modular, cross-platform and decentralized workflow automation framework with a human-friendly interface and reusable automation recipes to make it easier to compose, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data, software and hardware
guildai - Experiment tracking, ML developer tools
fastapi-template - Completely Scalable FastAPI based template for Machine Learning, Deep Learning and any other software project which wants to use Fast API as an API framework.
dvc - 🦉 ML Experiments and Data Management with Git
experta - Expert Systems for Python
tensorflow - An Open Source Machine Learning Framework for Everyone