DataHour: Explainable AI - Need and Implementation

Today AI powered by ML is mainstream in several businesses across verticals. However there is skepticism in certain verticals on the power of ML to be able to perform complex tasks without a rationale of "Why is the ML model giving this result"?

This question haunts scenarios like a ML model taking decisions in credit cards in BFSI or taking decisions on cancer in Healthcare etc. To allow for answering such questions the area of Explainable AI (XAI) was introduced which is able to provide explanations for the decisions made by the ML model. In this DataHour, Neelima will provide a hands-on intro to XAI.

Prerequisites:Enthusiasm to learn Data Science.

Neelima Vobugari is a seasoned entrepreneur with extensive IT experience of over 20 years. She is a certified Data Scientist with a degree in data science from John Hopkins University, Maryland, USA. She has a MBA from Symbiosis and a B Tech from JNTU. Her entrepreneurial stint is focused on consulting and training in area of data science and Artificial Intelligence and related technologies. She is currently CEO of Tarah Technologies, a marquee AI and Machine Learning competency and consulting firm. Her IT experience span giant IT companies including IBM. She is now embarking on an innovative product in AI space via testAIng.comShe has recently been conferred the prestigious "Women in AI" award given to select women leaders in data science and AI.She is a strong innovator, has filed three patents in area of AI, and provided innovative solutions to over 20 AI consulting projects at marquee clients. She has the distinction of having trained over 2000 students and professionals via various enterprise and B2C trainings in various areas of data science, AI and machine learning. Her trainings have been well received by students as well as corporate employees.