Shivani Poddar
Shivani Poddar is a Machine Learning Tech Lead for the Meeting Assistant team at Workplace, Facebook, leading the development of meeting assistants for making remote collaboration easier for work. Previously, Shivani built and launched the foundational machine learning and AI stack for Facebook Portal, spearheading product and engineering development across social graph technology for ML, deep personalization for a smarter calling experience.
She was also the first ever student at Carnegie Mellon to be funded by the Amazon Alexa Prize, where she and her team built a social chatbot, eventually deployed to tens of thousands of users through Alexa. During her time at CMU she also pursued research in the field of Natural Language Generation, Reinforcement Learning for chatbots and multimodal machine learning.
Outside of Work, Shivani has emerged as one of the leaders in talking about Artificial Intelligence and Machine Learning for Consumers as well as Enterprises. She has been a speaker at numerous conferences over the last 2 years covering topics such as – Diversity and Bias in AI, Future of Work, Immersive Multimodal Assistants. She is also a mentor for young aspirants looking to become the next innovators in the field, and regularly volunteers in resume building workshops, panels for hiring and Q&As on LinkedIn.
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How to Machine Learn-ify any Product
ML conf EU 2020
33 min
How to Machine Learn-ify any Product
This talk will be a walkthrough of utilizing machine learning to replace a rule based system for consumers. We will discuss when is it okay to use ML, how to build these models with intelligent data, evaluate these offline and finally how to validate this evaluation to land these models in production systems. Furthermore, we will illustrate various self-learning/interactive-learning strategies that can be used for production systems to automate how models teach themselves to become better.