A total of 33 academic staff and students from the University of Mauritius (UoM) had followed a training in Deep Learning in December 2019, delivered by Associate Professor Dr. Willie Brink from Stellenbosch University, South Africa. This project was approved under the AI Skills Development Programme set up by the Human Resource Development Council (HRDC).
The training culminated to mini projects which were worked out collaboratively amongst students and academics.
With a view to showcasing four of these mini-projects, UoM in collaboration with the HRDC organised a webinar on 17 September from 10 00 hrs to 11 30 hrs. The presentations were delivered by four participants comprising academic staff and students who took part in the training:
PROJECT
|
PROJECT TITLE |
BY |
Project 1 |
Determine whether an email message is SPAM or NOT SPAM |
Dr. Maleika Heenaye-Mamode Khan |
Project 2 |
Determine whether an image is a picture of a DOG or a CAT |
Mr. Inshirah Rossan |
Project 3 |
Determine whether energy usage of a building will go UP or DOWN
next month, using a time series of past energy usage values
|
Mr. Yashvinee Ahku |
Project 4 |
Identification of fashion clothes out of 10 different types |
Mrs. Zahra Mungloo-Dilmohamud |
Around 20 participants from both public and private institutions attended the webinar.
Click here to download the Webinar Presentation
About the training
The objectives of the training in Deep Learning (DL) were to:
- provide students and lecturers with the opportunity to upgrade their skills and knowledge in DL which is an industry focused technology;
- improve the employability of ICT graduates;
- build internal capacity of the University academic staff in deep learning for transfer of knowledge; and
- link the university to advanced foreign resources in DL to raise the level of academic staff and students in DL.
Students with IT/Mathematics/Engineering backgrounds having followed this course can work in all the areas requiring deep analysis and evaluation of data (such as classification, clustering among others). These students can work in the IT industries, banking and finance, and others.
Academic staff competent in DL can in turn integrate some aspects of DL in modules as well as act as resource persons locally.
Background Information
The field of artificial intelligence is essentially when machines can do tasks that typically require human intelligence. It encompasses machine learning, where machines can learn by experience and acquire skills without human involvement. Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data.
To meet the demands that are created by burgeoning industries and digitalisation of existing industries, there is need for a proactive and flexible approach to drive development over the few coming years. These shifting trends demand investment in development of skills and increase in AI talents in Mauritius spanning across university students, existing employees, unemployed youth and the society at large. The ‘Mauritius Artificial Strategy 2018’ has highlighted that the lack of talent and qualified workers in Mauritius is a deterrent to the implementation of AI across business operations.
Hence, in line with the need to build local capacity in AI, UoM solicited the services of Dr. Willie Brink, to train the 30 participants. Students with backgrounds in IT/Mathematics/Engineering, having followed this course, would be able to work in all the areas requiring deep analysis and evaluation of data (such as classification and clustering). These students can work in IT industries, banking and finance, among others. Academic staff competent in Deep Learning can in turn integrate some aspects of Deep Learning in modules as well as act as resource persons locally.
Definition and Applications of Deep Learning (DL)
Artificial intelligence is a data-driven technology that is both powering autonomous machines and augmenting the flow of information and analysis for human workers. As machine learning evolves, workers must learn to adjust in much the same way as adapting to a new tool or software service. DL is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from data. Also known as deep neural learning or deep neural network, Deep Learning method are based on learning data representations, as opposed to task-specific algorithms.
Deep Learning is required in many fields and to build smart applications. For example Google's search engine, voice recognition system and self-driving cars all rely heavily on deep learning. They have used deep learning networks to build a program that picks out an attractive still from a YouTube video to use as a thumbnail.
Deep learning is a novel and complex area and requires expert training. The very first step is to understand the foundations of DL and gain hands-on experience from experts.