Tutorial 1 - Hands-on Deep Learning for Industrial Informatics Applications

Tutorial Session Presented by

Daswin De Silva, Rashmika Nawaratne, and Achini Adikari


Deep learning is a persistently maturing artificial intelligence paradigm in research and practice. It maintains a formidable evidence base and increasing potential for applications in the industrial informatics of automation, energy, manufacturing, transport, communication and human engagement. This workshop aims to develop essential knowledge of deep learning and key skills in industrial applications, with hands-on tutorials in Python IDE, using Google Colab and Jupyter Notebook. The workshop will begin by exploring the structural elements of deep learning models, hyper-parameters, and comparison to standard machine learning algorithms, followed by the theory and application of deep neural networks (classification), convolutional neural networks (image processing), and deep recurrent neural networks (time-series prediction). Attendees will attempt hands-on experiments with each technique using a benchmark dataset, for training, testing and evaluation. Tutors will also demonstrate each technique in the context of separate real-life projects, with emphasis on deliverables to industry stakeholders. Upon completion of the workshops, attendees will know theoretical foundations of deep learning, when to use and in which industrial settings, how to develop a deep learning model, implement, test and deploy the model as an algorithm in Python IDE

Bio of the presenters

Daswin is AI Platforms specialist in the Research Centre for Data Analytics and Cognition (CDAC) at La Trobe University, Australia. Daswin’s research interests are incremental machine learning, information fusion, deep learning, auto ML, with applications in energy, smart cities, and human emotions. He’s an associate editor of the IEEE Transactions of Industrial Informatics. Rashmika and Achini are Project Leads in the same Research Centre (CDAC). Rashmika leads the image, video analysis capability with applications in transport while Achini leads the human sentiment and emotions analysis with applications in digital health and social media. Besides academic pursuits, as part of CDAC strategic initiatives, all three presenters are actively involved in industry engagement, solving real-world analytics problems and working with both analytics technology providers and consultants.