Process split datasets into training, validation, and testing sets for ML model development. Use when requesting "split dataset", "train-test split", or "data partitioning". Trigger with relevant phrases based on skill purpose.
npxskills add jeremylongshore/claude-code-plugins-plus-skills--skill splitting-datasetsLoading…
Split datasets into training, validation, and testing sets with configurable ratios and stratification options.
This skill automates the process of dividing a dataset into subsets for training, validating, and testing machine learning models. It ensures proper data preparation and facilitates robust model evaluation.
This skill activates when you need to:
User request: "Split the data in 'my_data.csv' into 70% training, 15% validation, and 15% testing sets."
The skill will:
User request: "Create a train-test split of 'large_dataset.csv' with an 80/20 ratio."
The skill will:
This skill can be integrated with other data processing and model training tools within the Claude Code ecosystem to create a complete machine learning workflow.
The skill produces structured output relevant to the task.
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Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).