Machine Learning with Amazon SageMaker
Event description
Brought to you by QCIF in partnership with Amazon Web Services and delivered by Amazon Web Services Senior Solutions Architects, this workshop will give you an comprehensive introduction to Machine Learning, one of the most exciting techniques in computational data analysis, using Amazon SageMaker.
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this workshop, we will explore the fundamentals of Machine Learning from a practical perspective with the help of Amazon SageMaker. Amazon SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning models for any use case with fully managed infrastructure, tools, and workflows.
We will explain the fundamentals of Machine Learning on Amazon SageMaker, and will use real world datasets to demonstrate its use. After these hands-on workshop, you will have a better understanding of Amazon SageMaker techniques and be able to accelerate your research projects outputs.
The Amazon SageMaker workshop will be hosted at the Brisbane AWS offices (Level 30, 300 George St, Brisbane) and virtually. For those attending in person, catering will be provided.
Please note, this event is only open to participants from QCIF member universities.
FAQs
What should I bring into the event?
You will need to provide your own laptop with a up-to-date web browser installed (Chrome or Firefox preferred).
What prior experience do I need?
Participants should have an understanding of Machine Learning principles and techniques. Previous experience with Python is highly recommended.
Who should attend?
All researchers interested in using the Amazon Web Services cloud for the application of Machine Learning techniques to research data analysis.
How can I contact the organiser with any questions?
You can email training@qcif.edu.au
What's the cancellation policy?
Cancellations are accepted up to three working days before the start of the workshop. If you do not join on the day without having cancelled beforehand, you may be blocked from attending any future QCIF training workshops.