In today’s demanding market, Machine Learning capabilities have become a basic requirement you need to support. Self-service BI solutions are no different. Users need machine learning capabilities as an integral part of the provided solution.
The specific challenges of integrating ML capabilities in a self-service BI platform include the supply of ML algorithms that do not rely on specific data and can be easily applied and fit to customer specific use cases (and data).
In this Data Science Central Webinar we will demonstrate how to implement a classification model in a generic manner that can be used by many customers, without relying on specific data, and by automating the validation process ensuring minimum overfit introduced. It will outline the challenges in such a scenario and ways to mitigate them. Specifically, the case study will demonstrate implementing a Decision Tree model and visualize it using a dynamic UI component.
Speakers:
Nir Regev, Senior Data Scientist, Data Scientist Team Leader — Sisense
Evan Castle, Product Manager — Sisense
Hosted by:
Bill Vorhies, Editorial Director — Data Science Central
