clearml
nestedcvtraining
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clearml | nestedcvtraining | |
---|---|---|
20 | 6 | |
5,169 | 27 | |
2.8% | - | |
8.1 | 0.0 | |
4 days ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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.
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
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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!
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[D] Facebook Visdom vs Google Tensorboard for Pytorch
I'm talking about ClearML😅 trying not to shill for open-source but ~5000 teams have already chosen 💪 https://github.com/allegroai/clearml
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[D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit? -> MY OWN CONCLUSIONS
There are mainly two solutions that are 100% open source and free to install and use, and that may solve most of the requirements of ML practitioners: Hopsworks and ClearML. Among this two, if I had to chose one right now, it will be ClearML. Hopsworks might be much more complete, but ClearML seems to have a bigger community behind it and to be easier to install and use. So ClearML will be something to take a look at in case we go for an all-in-one package. I also like the idea of having a platform with an UI with all our projects.
- [D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit?
nestedcvtraining
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[D] Andrew Ng's data-centric vs model-centric Machine Learning
Once you have your pipeline, model included, with all the transformers defined and parametrized, you could use an optimizing approach like the one in the examples of this library: https://github.com/JaimeArboleda/nestedcvtraining Do you think it will be a good idea? Or am I oversimplifying?
- [D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit?
What are some alternatives?
MLflow - Open source platform for the machine learning lifecycle
BentoML - Build Production-Grade AI Applications
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
kedro-great - The easiest way to integrate Kedro and Great Expectations
streamlit - Streamlit — A faster way to build and share data apps.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
feast - Feature Store for Machine Learning
aws-mlu-explain - Visual, Interactive Articles About Machine Learning: https://mlu-explain.github.io/
metaflow-on-kubernetes-docs - Documentation For Running Metaflow on Kubernetes
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Python Packages Project Generator - 🚀 Your next Python package needs a bleeding-edge project structure.
determined - Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.