Applied AI Toronto Session #1
6:00pm to 6:30pm - Welcome and networking
6:30pm to 7:00pm - Automated Detection of Social Media Preferences
7:00pm to 7:30pm - Reimagining Working with Data
7:30pm to 9:00PM - Networking
Title: Automated Detection of Social Media Preferences
There is a disparity between privacy-related intentions and behaviours among social media users. Despite consumer willingness to post and share online, brands are at risk when dealing with social media data, even when the data is publically available and voluntarily disclosed.
Taraneh Khazaei of Zero Gravity Labs presents a novel graph-based machine learning approach to discover privacy preferences of social media users. Previously introduced at the World Wide Web (WWW) conference and the social media conference of the Association for the Advancement of Artificial Intelligence (AAAI); the presentation concludes with a discussion of broader applications of the technique, outside of privacy preference discovery.
Target audience: Technical and non-technical
Taraneh is currently a data scientist at Zero Gravity Labs, aiming to push the boundaries of artificial intelligence and machine learning. She has a PhD degree in computer science, where she focused on a variety of machine learning and statistical modelling methods in the context of natural language processing, social computing, and online privacy mining. Before joining Zero Gravity Labs, she worked at TD bank as a data scientist/engineer and at InfoTrellis as a machine learning researcher.
Title : Reimagining Working with Data
Over 2.5 billion GB of data is generated everyday. Businesses harness this data to obtain insights and improve their products. However, dealing with the sheer volume and variety of data can be a daunting task, often requiring teams of data scientists and IT professionals to manage the data. These data experts often rely on special tools to manage data, and even with these tools, working with data is time consuming and very expensive. What if there was an easier way to work with data? What if data tools were made more intuitive and intelligent? AI based tools can supercharge existing processes, and even empower business users to work with data.
In this presentation, we will describe the data processing pipeline that broadly consists of three steps : data collection, data cleaning and data analysis. Various business use cases will be discussed for each step, comparing older processes with newer, AI based processes. We conclude by showing that AI based tools outperform older tools and businesses have a lot to gain by embracing AI based technology.
Technical and non-technical
Dhruv Gairola is the founder of Datachili, a platform that uses machine learning to improve data quality. He has an MSc in computer science from McMaster University, specializing in Data Cleaning research. He is interested in cutting-edge technology and its potential to solve business problems. In his spare time, Dhruv enjoys traveling and playing the electric guitar.
Thank you to our host Zero Gravity Labs who is providing a venue and refreshments (food and pop) for the event.
As the innovation arm of LoyaltyOne, Zero Gravity Labs focuses on the future of customer influence. We moved to a startup-friendly office space outside of the corporate environment to allow us to explore and experiment without the limitations or constrictions of today’s business and technology realities.
We explore ways to change the face of loyalty and customer experience within the retail and banking industries, using emerging technologies identified through a process of ideation, experimentation and real world testing.