La Trobe University is hosting the 3rd International Conference on Big Data and Internet of Things (BDIOT 2019).
- Thursday 22 August 2019 09:00 am until Saturday 24 August 2019 06:00 pm (Add to calendar)
- Jasmine Nieh
- Presented by:
- La Trobe University
- Type of Event:
The BDIOT 2019 conference is co-located with the 2019 International Conference on Virtual Reality and Image Processing (VRIP 2019).
The rapid advancement and ubiquitous penetration of mobile network, web based information creation and sharing, and software defined networking technology have been enabling sensing, predicting and controlling of physical world with information technology. Every business process can be empowered, and therefore, various industries redesign their business models and processes along Internet of Things (IoT) paradigm.
The main purpose of BDIOT 2019 is to provide an international platform for presenting and publishing the latest scientific research outcomes related to the topics of Big Data and Internet of Things.
Please visit the BDIOT website for more info here.
Mr Rashmika Nawaratne and Mrs Achini Adikari from LBS' Centre for Data Analytics and Cognition (CDAC) will give a presentation titled "Hands-on Deep Learning for Big Data & IoT Applications"
About the workshop
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 Big Data and IoT environments in energy, manufacturing, transport, communication and human engagement. This workshop aims to develop essential knowledge of deep learning and key skills in industrial applications using Big Data and IoT, with hands-on tutorials in Python, using Google Collaboratory 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 which accommodate Big Data and IoT data. 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.
Information on fees and tickets and registering for the conference can be found and done here.
La Trobe City Campus
360 Collins Street, Melbourne, 3000
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