EE 3700-0

Brief

The course provides an introduction to machine learning. The course will provide an overview to machine learning ranging from statistical-based method, discriminant-based method, multi- layer perceptron to contemporary deep learning method. It also includes hands-on exercises.

Description

Course description: The course provides an introduction to machine learning. The course will provide an overview to machine learning ranging from statistical-based method, discriminant-based method, multi-layer perceptron to contemporary deep learning method. It also includes hands-on exercises. Textbook: Introduction to Machine Learning, Fourth Edition, Ethem Alpaydin Teaching Method: Lecture Syllabus (Tentative): Section 1 Introduction to Machine Learning Supervised Learning Bayesian Decision Theory Parametric Model Multivariate Methods Section 2 Clustering/Dimension Reduction Decision tree Linear Discrimination Support Vector Machine Section 3 Multilayer Perceptron Deep learning Design and Analysis of Machine Learning Experiment Invited Lecture Nvidia DLI – Hands on lecture Website: We will use eelearn

Prerequisites

Timetable

Scores

Average Percentage 84.53

Std. Deviation 10.16

Remarks

非常態開設課程。

Restrictions

電機系大學部3年級4年級,電資院學士班大學部3年級4年級優先，第3次選課起開放全校修習

Compulsory

Elective

Cross Discipline

First Specialization

Second Specialization