Machine Learning Using Python

Catalog description

Course offers a comprehensive overview of machine learning fundamentals. It covers key concepts and techniques, including supervised, unsupervised and reinforcement learning. Core topics include data processing, linear regression, k-means clustering, support vector machines, decision trees, random forests, naive Bayes classification, and an introduction to neural networks. Students will apply their knowledge and skills to solving real-world problems while gaining hands-on experience with various Python tools for machine learning.