tournament-autoresearch
CommunityEnhance machine learning research with an autonomous tournament loop.
Authorgaasher
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the process of autonomous machine learning research, pressure-testing competing ideas before investing compute resources, by organizing a tournament loop that continuously improves over time.
Core Features & Use Cases
- Autonomous ML Research Loop: Compares and selects the best architecture changes for machine learning models through a tournament loop.
- Continuous Improvement: The loop's judge learns to pick better changes over time by scoring its own predictions against realized metric deltas.
- Use Case: Ideal for exploring open-ended ML experimentation where it's crucial to vet ideas before spending compute resources.
Quick Start
Run the tournament-autoresearch skill with the specified metric and parameters, and let it run until manually interrupted.
Dependency Matrix
Required Modules
python
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: tournament-autoresearch Download link: https://github.com/gaasher/Agent-Loop-Skills/archive/main.zip#tournament-autoresearch Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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