Low-code AI with MATLAB

Overview

This webinar will show you real-world examples how MATLAB makes AI easy and accessible with tools such as interactive apps generating MATLAB code. MATLAB provides AI capabilities similar to those of dedicated AI tools like scikit-learn or TensorFlow—and more importantly, only MATLAB lets you integrate AI into the complete workflow for developing a fully engineered system, from data preparation to deployment.

Highlights

• Generate MATLAB code using Apps comparing different machine learning methods   
• Graphically create, edit, and train Deep Learning models 
• Use labeller apps to automate your data labelling workflow
• Deploy your models to production in a variety of formats

About the Presenters

Dr Emmanuel Blanchard is a senior application engineer at MathWorks who first joined the company as a training engineer in 2014. He focuses on data analytics. Prior to joining MathWorks, he was a Lecturer in Mechatronic Engineering at the University of Wollongong. He holds a PhD in Mechanical Engineering from Virginia Tech. He also worked as a Systems / Controls Engineer at Cummins Engine Company and as a research assistant in several research institutions in California and Virginia. 

Dr Peter Brady is a Senior Application Engineer with MathWorks striving to accelerate our customer’s engineering and scientific computing workflows across maths, statistics, finance and machine learning. Prior to joining MathWorks, Peter worked in computational fluid and thermodynamics as well as high performance computing for a number of defence and civil contractors as well as a few universities. He has worked in fields as diverse as cavitation, wave/turbulence interactions, rainfall and runoff, nano-fluidics, HVAC and natural convection including scale out cloud simulation techniques. Peter holds doctorate in free surface computational fluid dynamics and a Bachelor of Civil Engineering both from the University of Technology Sydney and is a Chartered Practicing Engineer in Australia.