ClearML is a versatile, open-source machine learning operations (MLOps) tool that provides seamless integration with existing workflows. It’s designed to automate and accelerate machine learning and deep learning engineering processes, making them more accessible and manageable. ClearML offers a range of features, from automating resource management and data pipelines to tracking experiments and results.
It’s compatible with a wide variety of programming languages and platforms, including Python, Jupyter notebook, and PyTorch, to name a few. ClearML allows users to track, manage, and control every aspect of their machine learning projects, including data, configuration files, and code.
The platform also provides a web-based interface, ClearML Server, that enables users to monitor and manage their projects remotely. Users can visualise data, compare experiments, and share results with their team. Additionally, ClearML can be integrated with existing MLOps stacks to enhance workflow efficiency.
ClearML’s comprehensive documentation provides detailed instructions and examples to help users get started and make the most of the platform. It covers everything from installation and configuration to using the ClearML Python Package and integrating ClearML into existing workflows.
Go to source article: https://clear.ml/docs/latest/docs/