Webinar – Discover Mitra’s AWS ML Models: Part 2
14th Feb 2019 - 14th Mar 2019, 11am - 12pm
Description:
This is the next instalment in a series of webinars on Mitra Innovation’s new Machine Learning models on Amazon Web Services (AWS) Machine Learning Marketplace. The AWS ML Marketplace was introduced in November 2018 at the AWS annual learning conference, re:Invent, which had more than 30 partners involved in the launch of the new online marketplace, including Mitra.
Having released three models as part of the marketplace launch, Mitra now has four ML models published on the AWS Marketplace including the ‘Abusive Text Detector’ model that was covered in our previous webinar. In this session will go through the other three ML models, giving you an overview of how they work, their use cases and how to subscribe to them via the AWS Marketplace.
- Bitcoin price predictor, which uses past price trends to help you buy and sell your cryptocurrency with increased confidence.
- Diabetes detector, which allows you to identify whether someone is likely to be diabetic based on parameters such as age, BMI, glucose levels and blood pressure.
- Neural style transfer model, which can combine an image with a style/design from another image to give a composite image with a styling effect. This can be used in artwork applications such as logo and icon creation or fabric design generation.
Presenter 1:
Dileepa Jayakody – Research and Development Team Leader
Dileepa is the Research and Development team leader at Mitra Innovation. He is passionate about research and development and currently doing research in machine learning, natural language processing and artificial intelligence domains. He is also an open source software enthusiast and a committer in the Apache Software Foundation
Presenter 2:
Justus Nithushan – Research and Development Intern
Justus is a computer science engineering undergraduate at Jaffna University and is currently working with Mitra’s research and development team on new and exciting projects. His interests are in machine learning and data engineering.
