cascade
clearml
| cascade | clearml | |
|---|---|---|
| 9 | 20 | |
| 16 | 5,279 | |
| - | 2.1% | |
| 9.3 | 7.7 | |
| 6 days 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.
cascade
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modeldb VS cascade - a user suggested alternative
2 projects | 12 Dec 2023
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Sacred VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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keepsake VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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aim VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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guildai VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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metaflow VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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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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Announcing Cascade
This is Cascade - very lightweight MLE solution for individuals and small teams
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?
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
MLflow - Open source platform for the machine learning lifecycle
NVTabular - NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
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!
powershap - A power-full Shapley feature selection method.
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
kedro-great - The easiest way to integrate Kedro and Great Expectations
ds2 - Easiest way to use AI models without coding (Web UI & API support)
streamlit - Streamlit — A faster way to build and share data apps.
FeatureHub - The most comprehensive library of AI/ML features across multiple domains. Our goal is to create a dataset that serves as a valuable resource for researchers and data scientists worldwide
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️