MCP_cloudera
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The Cloudera ML Model Control Protocol (MCP) is a Python-based integration that allows interaction with Cloudera Machine Learning services programmatically.
The Cloudera ML Model Control Protocol (MCP) is designed to facilitate seamless interaction with Cloudera Machine Learning (CML) services. It provides a comprehensive suite of tools for managing machine learning projects, including uploading folders, creating and managing jobs, retrieving project IDs, and handling model deployments. The MCP is highly configurable, allowing users to set up their environment with ease using environment variables or direct code configuration. It supports a variety of operations such as experiment tracking, application management, and more, making it a versatile tool for data scientists and developers working within the Cloudera ecosystem.
Features
- Upload Folders: Upload entire folders to your CML project while preserving directory structure.
- Create Jobs: Create new CML jobs with customizable settings.
- List Jobs: View all jobs in your project with their current status.
- Delete Jobs: Remove individual jobs or all jobs in a project.
- Model Management: Create, list, and manage ML models and deployments.
