AI - Deep Learning

BCS (Bedford)

DateMonday 15 Mar 2021
Time

18:45 for 19:00-20:30

Location

Online meeting - We'll send the connection details on your confirmation email, once you have booked.

SpeakerMr. George Yazigi, Digital Systems Manager, DARTeC, Cranfield University
Abstract

Moore’s Law which sustained the exponential progress in Microelectronics in the past five decades is expected to come to an end by 2022. Concentrating billions of transistors on a chip has led to an unprecedented growth in Artificial Intelligence research particularly in Machine Learning and Deep Learning. However, unless new technology is invented, this growth may not be sustainable at the current rate in the future!

Deep Learning

Deep Learning is a sub-branch of Machine Learning focusing on algorithms inspired by the structure and function of the human brain called Artificial Neural Networks [ANN for short] and primarily relying on innovative coding techniques and advances in microelectronics to achieve unprecedented inferences results.

Let’s explore how Machine and Deep Learning can help in forecasting outcomes. And experience a live experiment to predict certain COVID19 variables! For example when the pandemic would reach the final phase in the UK or the USA!

Profile

Mr. George Yazigi is currently the Digital Systems Architect and Manager at the Digital Aviation Research Centre (DARTeC), Cranfield University. He has more than 20 years of experience in software engineering, computer and data science, architecting and designing digital security systems and intelligent software platforms based on Big Data Analytics, Computational Intelligence and Machine Learning.

Notes

Our events are for adults aged 16 years and over. For overseas delegates who wish to attend the event, please note that BCS does not issue invitation letters.

Agenda
18:45 Sign in - Welcome - Networking
19:00 AI - Deep Learning - Predicting Covid19 variables – George Yazigi
19:50 Virtual Coffee/Tea break
19:55 Live IoT Experiment
20:15 Q & A and Networking
20:30 Close
Downloads

Flyer as docx or pdf

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