According to a recent report by McKinsey & Company, AI technologies will generate $50 trillion of value by the year 2025. The key to creating this value is leveraging operational data to extract new insights and drive executive decisions. As a result, businesses nowadays widely deploy predictive analytics and machine learning for predicting loan defaults, churn, fraud, insurance claims, hospital readmission, service outage, and many other cases. This workshop is about how business stakeholders can spot AI opportunities, drive AI projects in their organization, and create a tangible impact on the bottom line.
Audience: Business analysts, project managers, executives, engineers interested in industrial applications of AI
Speaker: Yuriy Guts, Machine Learning Engineer at DataRobot with 10+ years of experience in the industry
AGENDA- What can and cannot be achieved through predictive modeling
- How predictive models work in a nutshell
- How to define a predictive modeling project and criteria for its success
- Where to gather data and how to prepare it
- What expertise to involve and at what stages
ABOUT THE SPEAKER
Yuriy Guts is a Machine Learning Engineer at DataRobot. He has been working in data science, software engineering, and software architecture for over 10 years. He is passionate about applying machine learning to real-life use cases and democratizing data science among non-technical stakeholders. He teaches AI and ML at UCU (Computer Science and Data Science degrees), and has been an organizer or speaker at numerous data science events across Ukraine