Big Data & AI Toronto

October 6-7, 2022

Metro Toronto Convention Center

DataRobot at Big Data & AI Toronto 

Big Data and AI Toronto is an event that brings together a wide spectrum of minds from data scientists to CEOs. Connect with thousands of attendees in October 2022 to help you take your projects to the next level and build long term relationships with industry professionals

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Exhibit Location

  • Metro Toronto Convention Center

 

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Exhibit Hours

  • Thursday, October 6 – 8:30 AM – 5:00 PM
  • Friday, October 7 – 8:30 AM – 5:00 PM

Agenda

Thursday, October 6th

Time: 9:30 AM – 10:00 AM

Location: Big Data Demo Stage

Improve Anti-Money Laundering Programs with Automated Machine Learning

Reduce costs by improving the efficiency of AML transaction monitoring using Machine Learning. Compliance organizations within banks and other financial institutions rely on machine learning to improve AML compliance programs. Today, the systems that aim to detect potentially suspicious activity are commonly rule-based and suffer from ultra-high false positive rates. Automated machine learning provides a solution to address this challenge.

In this workshop, Data Scientist May Masoud will show how to use automated machine learning to reduce false positive rates. The results: improved efficiency of AML transaction monitoring and reduced costs.

Discover how Automated Machine Learning enables you to:

  • Develop and refresh AML predictive models in a timely manner
  • Deploy more accurate models with a click of a button
  • Operationalize AML models by following a user-centric process
May Masoud
May Masoud

Data Scientist, DataRobot


Thursday, October 6th

Time: 11:20 AM – 11:50 AM

Location: AI Stage

AI Everywhere: Canadian Tires’ Journey to Deep Value with DataRobot

AI adoption is at a tipping point. Many executives are rightly disillusioned about its potential to deliver value. They are either stuck in a cycle of experimentation, despite hefty investment, or they are struggling to scale AI’s impact beyond a handful of use cases. To realize deep value, organizations need to drive personnel growth, business growth and prepare for AI’s growth in society. When all three come together, organizations will have an engaged, thoughtful workforce, achieve AI maturity and scale that creates distance with competitors, and they’ll be prepared for macro-economic changes and even pending AI regulations.

In this session, Ricardo Baltazar from Canadian Tire will discuss their journey to increase AI fluency throughout the business. This personal focused journey has enabled Canadian Tire to scale AI quickly and effectively, increasing revenue while decreasing costs. To do so, DataRobot has acted as a trusted technology partner lowering AI barriers, adding standardized workflows and actively monitoring production AI. And, with complete visibility and transparency across all AI assets, you can realize deep value success with AI much faster. The partnership has led to AI Everywhere at Canadian Tire.

Ted Kwartler
Ted Kwartler

Field, CTO, DataRobot

Ricardo Baltazar

Associate Vice President, Innovation Lab, Canadian Tire Corporation


Thursday, October 6th

Time: 1:30 PM – 2:00 PM

Location: AI & Big Data Demo Stage

Accelerate feature engineering in Snowflake with DataRobot Automated Feature Discovery

Accelerate feature engineering by automatically generating hundreds of new valuable features across multiple datasets in Snowflake. Feature engineering is a critical part of the machine learning lifecycle that can determine the success or failure of an AI project. Designing, preparing, and testing impactful features poses significant challenges as these features are typically spread across different data sets. Using DataRobot Automated Feature Discovery, we will show how to test and create valuable new features for your machine learning models. This fast and straightforward option dramatically improves model accuracy and deepens your overall understanding of the problem at hand. 

In this workshop, Data Scientist May Masoud will show how Automated Feature Discovery integrates with Snowflake to make feature generation more accurate, faster, and cost-effective.

Learn how you can leverage Automated Feature Discovery to:

  • Discover meaningful features spread across different Snowflake datasets
  • Transform features to make them useful for models
  • Periodically recompute features with fresh data
May Masoud
May Masoud

Data Scientist, DataRobot


Friday, October 7th

Time: 10:30 AM – 11:00 AM

Location: Big Data Stage

From experimentation to value creation with AI

How do you move from experimenting with AI, to truly innovating and creating value? In this session, we’ll share three key learnings on how to solve real-world business problems and deliver tangible impact with AI, including:

  • The importance of planning and alignment on AI use cases
  • How to leverage AI model factories for scalable success
  • The powerful potential of AI Centers of Excellence

Plus, we’ll show how one DataRobot customer has realized success with transformational AI.

Chandler McCann
Chandler McCann

VP Data Science & Field CTO, DataRobot


Friday, October 7th

Time: 11:00 AM – 11:30 AM

Location: AI & Big Data Demo Stage

AI Governance Leads to Faster Value

Contrary to popular belief AI governance leads to increasing the number of deep value models in production. Governance doesn’t mean burdensome processes that slow an organization down. This presentation discusses emerging trends in the AI/ML space as well as best practices to realize value more quickly with the right type of AI governance.

Ted Kwartler
Ted Kwartler

Field, CTO, DataRobot