by Madiha Shakil Mirza | at Minnebar 17
A deep dive into what is Natural Language Processing (NLP), the various NLP applications and tasks, different approaches of solving Natural Language Processing problems (rule-based methods to Machine Learning, Deep Learning, and Transfer Learning), and a demo of some popular NLP models.
Madiha Shakil Mirza graduated from the University of Minnesota with a degree in Master of Science in Computer Science.
She was a Graduate Research Assistant and Graduate Teaching Assistant in the Department of Computer Science at the University of Minnesota. Her graduate thesis and research are in the field of Natural Language Processing (NLP), a sub-field of Artificial Intelligence. Her thesis “Language Models for Interpretation of English Puns” focuses on Computational Humor, a branch of NLP which uses Machine Learning and Deep Learning algorithms to create computers and conversational agents (voice assistants, chat bots) that have amusing personalities.
Her research on “A Feature Engineering Approach to Irony Detection in English Tweets” has been published in the Proceedings of The 12th International Workshop on Semantic Evaluation (2018), Association for Computational Linguistics, New Orleans, LA.
Does this session sound interesting? You may also like these:
This will add your name to the list of interested participants. It will help us gauge interest for scheduling purposes.