hyperparameter-tuning
De la autor
Optimize machine learning model hyperparameters using grid search, random search, Bayesian optimization, and Hyperband to maximize model performance within a compute budget. Use when the user requests hyperparameter tuning or provides relevant inputs for this workflow.
Instalare
npx skills add seb1n/awesome-ai-agent-skills --skill hyperparameter-tuning -a claude-code
Se instalează în .claude/skills/hyperparameter-tuning/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
Vrei ca agentul să-ți propună skill-uri în timp ce scrii? Vezi cum folosești skill-urile din IDE.
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 82
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- fit-tunetonone-ai/tononeDesign a hyperparameter tuning strategy for a model — search space, method, and budget. Use when asked to "tune hyperparameters", "define a search space", or "set a tuning budget".Design★ 76
- qdrant-performance-optimizationqdrant/skillsNavigation hub linking sub-skills for proactive Qdrant tuning: search speed, indexing performance, and memory usage optimization. Use when planning configuration or capacity changes to improve speed and efficiency. For diagnosing an active production slowdown or analyzing live metrics, use qdrant-monitoring instead.Planificare★ 263
- optimizing-performanceCloudAI-X/claude-workflow-v2Analyzes and optimizes application performance across frontend, backend, and database layers. Use when diagnosing slowness, improving load times, optimizing queries, reducing bundle size, or when asked about performance issues.Date★ 1.4K
- automl-hyperparameter-optimizationMindrally/skillsBest practices for AutoML and hyperparameter search with Optuna, Ray Tune, and PyCaret, covering search-space design, validation splits, and leakage prevention. Use when tuning model hyperparameters, setting up a pruned or distributed hyperparameter search, designing a nested validation scheme, or evaluating whether an AutoML leaderboard result is production-ready.Design★ 286
- performance-optimizationaddyosmani/agent-skillsOptimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.Design★ 110.1K
- performance-profilingnahid-sparktales/agent-dispatcherFind where the time actually goes before changing anything — define the metric and workload, build a repeatable baseline with its spread, profile on the right axis, confirm the suspected hotspot by removing its work, then re-measure under identical conditions. Use when something is slow, when an optimization is about to be written from a hunch, or when a speedup is being claimed without comparable numbers. Not for reading code to guess what is expensive, not for micro-tuning with no measured user impact, and not a licence to profile production without asking.Redactare★ 59
Note și recenzii
—
nicio recenzie
Ai încercat acest skill? Notează-l ca să-i ajuți pe alții. Autentifică-te
Discuție
Intră în discuție. Autentifică-te