Welcome

Welcome to Machine Learning course for the Year 2018! Use this page to gain access to the course resources and information. You have made a wise choice in learning about this important topic. We are going through the course step by step with real examples, and firmly grip on machine learning topics to apply them in a real life problem with confidence.

I hope that you will enjoy the course and gain confidence in Machine Learning at the end of this course.

Course Description

The course aims to cover a broad range of topics in Machine Learning with various examples that provide a firm grip on the topics. The topics covered by the course include: the principle of machine learning, various algorithms for classification and categorization, and theory that provides concrete understanding on the relevant topics.

Prerequisites

Students are expected to have 1) Knowledge of programming skill (Python) to carry out assignments, 2) Basic probability and statitical theory.

Course Objectives

	To grain a good grip on machine learning topics.
	To understand various machine learning algorithms.
	To apply the knowledge in a real life problem.

Teaching Methodology

Lectures will be given in English, and everything will be elaborated in detail step by step. You will have tutorial sessions to concrete your understanding on the subject.

Contact Details

Dr. Suyong Eum
OSAKA University Graduate School of Information Science and Technology
1-5 Yamadaoka, Suita, Osaka, JAPAN, 565-08. B606
Email: suyong[at]ist.osaka-u.ac.jp

Dr. Hua Yang
OSAKA University Graduate School of Information Science and Technology
1-5 Yamadaoka, Suita, Osaka, JAPAN, 565-08. B501
Email: h-yang[at]ist.osaka-u.ac.jp