ml-autoresearch

What problem does it solve?

This Skill automates the iterative research process for machine learning models, enabling users to optimize their models through continuous analysis and adjustment.

Core Features & Use Cases

• Autonomous ML Research Loop: Continuously iterates on model changes, guided by analysis and evidence.
• Analysis-First Approach: Focuses on analyzing model behavior to inform the next change.
• Literature Integration: Optionally integrates scientific literature to inform model changes.
• Use Case: Ideal for autonomous machine learning research campaigns, where each model change is based on analysis of the model's actual behavior and optionally grounded in scientific literature.

Quick Start

Use the ml-autoresearch skill to optimize a CIFAR-10 model by specifying the metric and setting the 'literature' to 'on'.