Dinesh has a Bachelors’s and Masters’s degrees in Energy Engineering from the Indian Institute of Technology, Bombay. He has an overall work experience of 4.5 years of experience in data analyses, machine learning, and NLP. Built end-to-end data pipelines and data tools for various enterprises. He is currently working as a Data Scientist at Walmart Global Tech India.
May 27, 2021 11:35 AM PT
With the advancements in Artificial Intelligence (AI) and cognitive technologies, automation has been a key prospect for many enterprises in various domains. Conversational AI is one such area where many organizations are heavily investing in.
In this session, we discuss the building blocks of conversational agents, Natural Language Understanding Engine with transformer models which have proven to offer state of the art results in standard NLP tasks.
We will first talk about the advantages of Transformer models over RNN/LSTM models and later talk about knowledge distillation and model compression techniques to make these parameter heavy models work in production environments with limited resources.