Toán cho học máy

Mathematics for Machine Learning

Tín chỉ: 3
Bậc: Bachelor
Thang điểm: 10
Điểm qua: 5

Mô tả

This course introduces the mathematical concepts and foundations needed to talk about the three main components of a machine learning system: data, models, and learning. Upon this course, students will be able to understand: • Foundametal concepts about matrices and matrix decomposition. • Concepts of gradients. • The basics of probability and some distributions. • Optimization to find maxima/minima of functions. • Dimensionality reduction using principal component analysis. • Classification in the context of support vector machines. Method of teaching and learning: Lecture and project based learning

Phân bổ thời gian

Study hour (150h) = 45 contact hours (60 sessions) + 1 hour final exam + 104 hours self-study

Nhiệm vụ sinh viên

- Students must attend at least 80% of contact slots in order to be accepted to the final examination. - Student is responsible for doing all exercises and assignments given by the instructor in class or at home. - Use a laptop in class only for learning purposes - Promptly access course websites for up-to-date course information

Công cụ

- Internet - Python Programme