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: Marine has 5+ years of experience as Data Scientist. She is skilled in Machine Learning techniques, Python, Rule-based models & AI. She has strong experience in Predictive and Descriptive Analytics, Fraud detection. She has done her Master's Degree, Msc Big Data Analytics for Business from IÉSEG School of Management. Accounting & Finance from McGill University, Hong Kong University of Science and Technology and Europe Business School.