Machine Learning Library in C++

Abstract

This project aims to develop a comprehensive and versatile machine learning library in C++ tailored to address the diverse needs of developers and researchers in the field. The library encompasses a robust set of core machine learning algorithms, encompassing supervised, unsupervised, and reinforcement learning techniques. Additionally, it incorporates essential data preprocessing tools to streamline data manipulation and feature engineering tasks, along with model evaluation capabilities crucial for assessing algorithm performance. The library's primary focus is on providing a rich suite of machine learning algorithms, This empowers users to effectively prepare data for training machine learning models. Additionally, the library provides tools for data splitting, and model evaluation to ensure reliable and robust model performance assessment.