# Machine Learning

YouTube MCP is an AI-based solution designed to enhance the YouTube content interaction experience through machine learning technology. It supports video search, subtitle access, and semantic search without using the official API.

This is an MCP server that provides a standardized interface for Scikit-learn models, supporting functions such as model training, evaluation, data preprocessing, and persistence.

This project demonstrates the training of a linear regression model using Claude and the Model Context Protocol (MCP) for an end-to-end machine learning workflow. Users only need to upload a CSV dataset, and the system can automatically complete the entire process of data preprocessing, model training, and evaluation (RMSE calculation).

The Linear Regression MCP project demonstrates an end-to-end machine learning workflow using Claude and the Model Context Protocol (MCP), including data preprocessing, model training, and evaluation.

The Groundlight MCP server is a service for creating and managing image detectors. It supports multiple detection modes, including binary classification, multi-class classification, and counting functions, and provides interfaces for image queries and result retrieval.