Applied Data Science for e-Commerce

Join Arul Bharathi for a look at the application of data science in ecommerce and how data science disrupts this industry in terms of consumer behaviour and experience. The session will cover:
Recommendation Systems - A conceptual walk-through of item-based, user-based collaborative filtering and content based filtering which are used prevalently in ecommerce
Consumer Behavioural Modelling - A code walk-through and live demo of using tree-based models to decode the general strata of user behaviour and its effect on retention and loyalty (including model building and evaluation of original ecommerce data set; Technology - Python, scikit-learn, fast.ai )
Deep Learning for User Experience - Arul will cover how companies such as Amazon and Alibaba leverage the state-of-the-art techniques of deep learning to enhance their revenue and consumer loyalty. He'll provide demos of performing product category classification and image-based recommendation systems (technology - PyTorch, fast.ai)
Arul is a Data Scientist, Co-Op student at Realtor.com and is a current graduate of the SFU Big Data Masters program.
What to bring: A $5 donation for Covenant House Vancouver
Pizza and drinks sponsored by Realtor.com.