機器學習

``Google's always used machine learning. In all the areas we applied it to, speech recognition, then image understanding, and eventually language understanding, we saw tremendous improvements.'' by John Giannandrea, then VP of Engineering, Google} In the last decade, machine learning has been applied to many real world problems successfully. It is considered as the most essential and fundamental knowledge for a data scientist. We introduce core concept of machine learning and several useful learning methods including linear models, nonlinear models, kernel methods, dimension reduction, unsupervised learning (Clustering) and deep learning. Also some special topics and applications will be discussed.

1. Mathematical analysis 2. Numerical Methods 3. Linear Algebra 4. Probability 5. Programming skills

My lectures on OCW https://ocw.nctu.edu.tw/course_detail.php?bgid=1&gid=1&nid=563

Homework: 30 % Final Exam: 40 % Final Project: A Kaggle Competition, 30 %

1. Ethem Alpaydin (2014), Introduction to Machine Learning, $3^{rd}$ Edition, ISBN: 978-0-262-028189 http://www.cmpe.boun.edu.tr/~ethem/i2ml3e/ 2. Catherine F. Higham, Desmond J. Higham (2018), Deep Learning: An Introduction for Applied Mathematicians https://arxiv.org/abs/1801.05894

聯絡方式

yuhjye@math.nctu.edu.tw