How Machine Learning Saved $25 million!

With the development of free, open-source machine learning tools like R, H2O, Spark, scikit-learn, Google’s TensorFlow and more, it has never been easier for companies of all sizes to harness the power of data. Machine learning is not a magic bullet, but it does have the potential to serve as a powerful extender of human intelligence. A successful implementation of machine learning algorithms in real life is not just about the best predictive algorithm, it is about the best algorithm that can be deployed, maintained and is cost effective. This presentation is about a success story in using machine learning algorithms in eCommerce by having a good team, a solid infrastructure for managing data from extraction to exploration and modeling and a robust toolbox like H2O for a seamless process of building, evaluating and deploying predictive models.

Saed Sayad has more than 20 years of experience in data science, machine learning and artificial intelligence and has designed, developed and deployed many business and scientific applications of predictive modeling. Saed's main research area is real time data mining and has been presenting a popular graduate data mining course at University of Toronto since 2001.

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Doors will open for snacks and networking at 6:00 pm and the presentation will begin at 6:30 pm.