11-10, 10:15–11:00 (America/New_York), Winter Garden (5th floor)
Data Scientists excel at turning data into insight using a wide range of advanced analytic tools. We introduce Taipy, the next-gen Python application builder to provide a low-code platform to turn those insights into production-ready applications. Taipy GUI for high-performance visualization and Taipy Core for data, scenario, and pipeline management work collaboratively to turn analytics into business value. This talk will provide an overview of these tools, focusing on the open-source release.
In order to deploy a project in production, the critical step in the life of a data-driven application (large-scale data or AI application) is typically not the analysis and modeling, but constructing a complete web application on top of the underlying analytic code that can provide value to the business.
Taipy Core provides four critical components; Data Nodes, Tasks, Pipelines, and Scenarios. Taipy Core extends the typical AI/ML concept of pipeline by adding smart scheduling and caching for data and scenario management. Complex workflows including those with parallelization can be built into Taipy Core pipelines allowing the creation of large-scale data applications.
Taipy GUI is a robust, responsive web-based visualization framework designed to handle the demands of production-scale data-centric applications.
This talk will provide an overview of the capabilities of Taipy GUI and Core through demonstrations and code examples. Attendees will depart with an understanding of the key concepts of Taipy, ready to turn algorithms into applications.
No previous knowledge expected
Martin Shell is VP Customer Success at Avaiga. Prior to Avaiga he has held numerous roles in development, consulting and technical sales for organizations including ILOG, Manhattan Associates and IBM. His focus has been working with organizations to fit appropriate analytical techniques to the solution of business problems and maximizing ROI. He holds an M.S. degree in Operations Research from M.I.T where his focus was Prescriptive Analytics/Decision Optimization