Introduction to Machine Learning


Discover and understand patterns using Machine Learning

Workshop Dates: Monday 14 May 2018 – Tuesday 15 May 2018

Click here to download the leaflet for this event.

This course aims to provide a practical and comprehensive guide to modern machine learning techniques. It provides the delegates a detailed understanding of the fundamental concepts of Machine Learning and its application to data science. Delegates will study important concepts in learning, gain knowledge on both classical and some of the advanced machine learning techniques, be able to synthesise solutions using machine learning paradigm, obtain practical experience with machine learning problems, and understand the inner working of machine learning algorithms. The course is delivered by experienced academics who have over 20 years of combined experience in this field.

Follow this link to register for this event. Places are limited to ensure close interaction at hands-on lab sessions.

This course contains three parts: introduction to data science and learning, unsupervised learning, and supervised learning.

  • Introduction to data science
  • Introduction to machine learning
  • Unsupervised learning: clustering
  • Unsupervised learning: dimensionality reduction
  • Supervised learning: discriminative analysis
  • Learning theory
  • Supervised learning: regression and logistic regression
  • Supervised learning: randomised decision trees
  • Supervised learning: support vector machine
  • Supervised learning: neural networks

All topics are facilitated with lab materials. Programming language:

  • Python
  • Matlab

Introduction to both programming languages are also provided in the course lab sessions.

This workshop is designed to provide a gentle but comprehensive introduction to machine learning. Basic programming experience and basic math background are useful. However, the topics are gradually introduced with detailed derivations to show the inner working of various techniques. Lab sessions provide step-by-step programming examples to show programming in machine learning.

Monday 14th May 2018

08:45-09:00 Arrival tea/coffee
09:00-09:05 Welcome & Introduction
09:05-10:45 Lecture
10:45-11:00 tea/coffee break
11:00-12:30 Lecture
12:30-13:15 Lunch
13:15-14:45 Lecture
14:45-15:00 tea/coffee break
15:00-17:00 Lab

Welcome desk opens from 8.45AM

Tuesday 15th May 2018

08:45-09:00 Arrival tea/coffee
09:00-10:30 Lecture
10:30-10:45 tea/coffee break
10:45-12:30 Lab
12:30-13:15 Lunch
13:15-14:45 Lecture
14:45-15:00 tea/coffee break
15:00-16:30 Lab
16:30-17:00 Discussion session

Welcome desk opens from 8.45AM

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