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Hands-On Machine Learning in R – Getting Started

September 14, 2017 | 6pm to 8.30pm | MAS Building

Graham Williams

Director of Data Science, Microsoft Asia, Singapore
Graham joined Microsoft recently after over 30 years as researcher, developer and educator in Artificial Intelligence, Machine Learning, Data Mining, Analytics and Data Science. He was previously lead Data Scientist for the Australian Government’s Center of Excellence in Data Analytics, Director of Data Science at the Australian Taxation Office, and Principal Research Scientist with CSIRO Australia. Over those 30 years he has also been an active contributor to the Open Source ecosystem with open source software projects across Emacs, Linux, Data Science, and R. Graham has authored many books, papers, Internet resources and software packages for data scientists. His latest book released in July 2017 introduces the Essentials of Data Science through a programming-by-example based approach to knowledge discovery in R. He maintains an extensive collection of R and Data Science resources on https://togaware.com.

Abstract

Machine learning underlies much of today’s technological advances driving enterprises who are embracing data and information to become knowledge-driven organisations. R is a popular ecosystem for Knowledge Discovery, Machine Learning and Data Science. It has grown over the past 20 years from a specialist tool for a handful of statisticians to an estimated 4 million users today. It provides a platform for building and deploying machine learning based models.  This tutorial will introduce, with a hands-on focus, the R ecosystem for Machine Learning and Artificial Intelligence. We will understand some of the most widely used machine learning algorithms, including decision trees, and explore how we build models R. The concepts of ensembles will also be introduced as the state-of-the-art classification learner. The tutorial will focus on hands-on learning so that all attendees will gain the experience to then continue with building such models on their own. A particular focus is on the use of readily repeatable template scripts for our tasks.

Details

Date/Time Thursday 14 September 2017, beginning with a light reception at 6pm

Venue MAS Theatrette, Level 16, Looking Glass, Level 11, MAS Building, 10 Shenton Way, Singapore 079117

RSVP on https://goo.gl/forms/duN9oipf3WGGgn2s1. Provide the info for entry into the venue. Due to limited capacity, we will send you a confirmation email if your registration is accepted.  Attendance will be recorded.

Preparation Bring your own laptop with your own internet connectivity (or Wireless@SG available on-site) for use of the X2Go application which you should also install. If you have no network connectivity then be sure to install R and Rattle and related packages prior to the session.

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