Abstract: The biggest challenges for developers of AI applications very often consist in building & delivering software to be used as a decision-making tool by operational staff. We will present how these challenges have been addressed using 2 successful projects: a cash flow prediction application (for one of Europe’s largest retailers) and a sales prediction app for a Quick Restaurant service. A novel Python Application builder, Taipy played an essential role in the success of these applications. We will highlight the core concepts and benefits of using such a framework in the context of real industrial AI applications.
At a time where Python and AI are fast becoming mainstream, Taipy dramatically boosts the Data Scientist / Python Developer’s productivity with:
- Highly interactive and powerful user interfaces.
- Scenario management
- Pipeline modeling and execution
What you will learn through this track keynote:
● Gaining knowledge about core concepts and benefits of using Taipy in the context of real
industrial AI applications and how it can boost productivity for Data Scientists and Python
● Learning about two successful projects done with Taipy and how their challenges were
○ A cash flow prediction app for a major European Retailer
○ A sales prediction app for a Quick Service Restaurant -
● Understanding the challenges faced by developers when building and delivering AI applications
for operational staff to use as decision-making tools.
Bio: Albert has skills in machine learning and big data to solve (financial) optimization problems. He developed projects of different skill levels for Taipy’s tutorial videos.He got his degree from McGill University - Bachelor of Science. Major in Computer Science & Statistics. Minor in Finance.