research-time-series

What problem does it solve?

This Skill provides a comprehensive toolkit for tackling complex time series machine learning tasks, simplifying advanced analysis and prediction.

Core Features & Use Cases

• Versatile ML Capabilities: Supports classification, regression, clustering, forecasting, anomaly detection, and segmentation for time series data.
• Scikit-learn Compatible API: Integrates seamlessly with existing Python ML workflows.
• Use Case: Analyze sensor data to predict equipment failure (anomaly detection) or forecast sales based on historical trends (forecasting).

Quick Start

Use the research-time-series skill to perform time series classification on the loaded basic motions dataset.