APMTH 220 - Geometric Methods for Machine Learning Learning Course

[APMTH 220 - Geometric Methods for Machine Learning Learning Course] APMTH 220 - Geometric Methods for Machine Learning: APMTH 220 explores geometric and differential geometric techniques applied to machine learning and data analysis problems. Topics include manifold learning, kernel methods, and geometric deep learning architectures. The course emphasizes understanding the geometric structures underlying data sets and developing algorithms that exploit these structures for improved learning and inference. Through theoretical study and practical projects, students gain skills in designing and implementing geometric methods to tackle challenges such as dimensionality reduction, classification, and generative modeling in complex data sets. The course equips students with advanced tools for research and applications in artificial intelligence, computer vision, and computational biology. This Learning Course is a platform that helps students to study and learn. The platform provides all the required material for the students to study. The material includes Study guide, Exam Questions & Answers, Study Notes and other resources that are useful for the students. It also gives information about the upcoming exams so that students can prepare themselves accordingly.