prepare-dataset
Process and validate datasets for training. Use when setting up data pipelines.
npx skills add majiayu000/claude-skill-registry --skill prepare-dataset-mvillmow-projectodyssey-2 --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.
# Prepare Dataset Load, preprocess, and validate datasets for machine learning model training including normalization and augmentation. ## When to Use - Setting up data pipelines for training - Normalizing and cleaning raw data - Splitting into train/validation/test sets - Applying data augmentation ## Quick Reference ```python # Dataset preparation pipeline class DatasetLoader: def load(self, path: str) -> Tuple[ndarray, ndarray]: # Load raw data pass def normalize(self, data: ndarray) -> ndarray: # Normalize to [0, 1] or standardize pass def split(self, data: ndarray, ratios: Tuple[float, float, float]): # Split into train/val/test pass def augment(self, data: ndarray) -> ndarray: # Apply transformations if needed pass ``` ## Workflow 1. **Load raw data**: Read dataset from file (CSV, HDF5, NumPy) 2. **Validate data**: Check shape, dtype, missing values 3. **Preprocess**: Normalize, standardize, encode categorical features 4. **Split sets**: Create train/validation/test splits 5. **Augment data**: Apply transformations if needed (rotation, flip, etc.) ## Output Format Dataset preparation report: - Raw data shape and statistics - Data validation results (missing values, outliers)
- When to Use
- Quick Reference
- Workflow
- Output Format
- References
What does the prepare-dataset skill do?
Process and validate datasets for training. Use when setting up data pipelines.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill prepare-dataset-mvillmow-projectodyssey-2 --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 majiayu000/claude-skill-registry, a repository with 534 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.