training-machine-learning-models
Build train machine learning models with automated workflows. Analyzes datasets, selects model types (classification, regression), configures parameters, trains with cross-validation, and saves model artifacts. Use when asked to "train model" or "evalua... Trigger with relevant phrases based on skill purpose. '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill training-machine-learning-models --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.
# Ml Model Trainer Train machine learning models with configurable architectures, loss functions, and optimization strategies across classification, regression, and other task types. ## Overview This skill empowers Claude to automatically train and evaluate machine learning models. It streamlines the model development process by handling data analysis, model selection, training, and evaluation, ul
What does the training-machine-learning-models skill do?
Build train machine learning models with automated workflows. Analyzes datasets, selects model types (classification, regression), configures parameters, trains with cross-validation, and saves model artifacts. Use when asked to "train model" or "evalua... Trigger with relevant phrases based on skill purpose. '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill training-machine-learning-models --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.