tuning-hyperparameters
Optimize machine learning model hyperparameters using grid search, random search, or Bayesian optimization. Finds best parameter configurations to maximize performance. Use when asked to "tune hyperparameters" or "optimize model". Trigger with relevant phrases based on skill purpose. '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill tuning-hyperparameters --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Hyperparameter Tuner Optimize machine learning model hyperparameters using grid search, random search, or Bayesian optimization to maximize performance. ## Overview This skill empowers Claude to fine-tune machine learning models by automatically searching for the optimal hyperparameter configurations. It leverages different search strategies (grid, random, Bayesian) to efficiently explore the hy
What does the tuning-hyperparameters skill do?
Optimize machine learning model hyperparameters using grid search, random search, or Bayesian optimization. Finds best parameter configurations to maximize performance. Use when asked to "tune hyperparameters" or "optimize model". Trigger with relevant phrases based on skill purpose. '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill tuning-hyperparameters --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.