ClearML
Why Choose ClearML?
You should choose this if you're deep into machine learning and need a solid, open source MLOps platform that covers everything from experiment tracking to data ops and deployment. It's built by folks who really get data science and devops, making your ML projects easier and more efficient.
We’re an open source MLOps company that gives data scientists, ML engineers, devops practitioners and engineering managers the tools to do more with their machine and deep learning projects. We are a global team of people who value excellence and delivery, and we ♥ data, science, and devops. At ClearML, we are always looking for people who want to help, either in our open source project or join us as an employee. Want to know more? Visit www.clear.ml
ClearML Introduction
What is ClearML?
The key features of ClearML’s open source, end-to-end MLOPs Platform are: ClearML Experiment – ClearML Experiment allows you to track every part of the ML experimentation process and automate tasks. With it, you can log, share and version all experiments and instantly orchestrate pipelines. ClearML Orchestrate – With ClearML Orchestrate DevOps and data scientists are empowered through autonomy and control over compute resources. The cloud native solution also enables kubernetes and bare-metal resource scheduling with a simple and unified interface to control costs and workloads. ClearML DataOps – ClearML DataOps delivers data store automation. Automate data collection into searchable, accessible, and ML-ready data repositories through cutting-edge MLOps technology. ClearML Hyper-Datasets – ClearML Hyper-Datasets allows MLOps teams to build data-centric AI workflows. Make the most out of unstructured-data using queryable datasets, made possible through ClearML Hyper-Datasets. ClearML Deploy – ClearML Deploy delivers a unifying model repository, custom pipelines, and model serving. This allows MLOps teams to Transition from model development to production and gain full workflow visibility with seamless integration to the experiment manager and orchestration. Every component of ClearML integrates seamlessly with each other, delivering cross-department visibility in research, development, and production.
How to use ClearML?
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Why Choose ClearML?
You should choose this if you're deep into machine learning and need a solid, open source MLOps platform that covers everything from experiment tracking to data ops and deployment. It's built by folks who really get data science and devops, making your ML projects easier and more efficient.
ClearML Features
Features
Feature information not available.
Pricing
Free
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- ✓ Open Source, End-to-End MLOPs Platform