prepare-dataset

What problem does it solve?

This Skill streamlines the process of preparing raw data into a format suitable for machine learning model training, ensuring data quality and consistency.

Core Features & Use Cases

• Data Loading: Reads data from various file formats (CSV, HDF5, NumPy).
• Validation: Checks for data integrity, including shape, dtype, and missing values.
• Preprocessing: Normalizes, standardizes, and encodes features.
• Splitting: Divides data into training, validation, and testing sets.
• Augmentation: Applies transformations to increase dataset diversity.
• Use Case: Prepare a large image dataset by normalizing pixel values, splitting it into training and testing sets, and applying random rotations to the training data.

Quick Start

Use the prepare-dataset skill to load data from '/data/raw_images.zip', normalize it, and split it into 80% training and 20% testing sets.