DataHour: Explainable AI: Demystifying the Black Box Models

Join this DataHour for an in-depth exploration of Explainability in AI (XAI). Discover its significance, types of explanations, and when it's needed. Learn about glass box, white box, and black box models, and explore popular XAI techniques like LIME, SHAP, DiCE, and more. See how XAI is applied in real-world scenarios. Whether you're a data scientist or just curious about XAI, gain valuable insights to enhance your AI projects. Don't miss this opportunity to demystify XAI!

Dr. Farha Anjum Khan is a seasoned data scientist with a passion for bridging the gap between technology and responsible AI. With a career spanning six years in the field of data science, she brings a wealth of knowledge and experience to the table.Dr. Khan's journey into data science was preceded by her academic pursuits in experimental nuclear and particle physics. She honed her skills while working at the prestigious synchrotron center in Forschungszentrum Jülich, Germany, and the University of Wuppertal, Germany. It was during her doctoral research that she delved deep into the world of data, algorithms, and artificial intelligence, sparking her fascination with these domains.