Natural language processing with deep learning
Module: 5. Policy Analysis Concentration Elective | 6. Portfolio Elective
Instructors: Prof. Slava Jankin, PhD, Dr. Hannah Béchara
Abstract
Natural language processing (NLP) is a key technology of the information age. Automatically processing natural language outputs is a key component of artificial intelligence. Applications of NLP are everywhere because people and institutions largely communicate in language. Recently, statistical techniques based on neural networks have achieved a number of remarkable successes in natural language processing leading to a great deal of commercial and academic interest in the field. This course provides an overview of modern data-driven models towards richer structural representations of how words interact to create meaning. We will discuss salient linguistic phenomena and successful computational models. We will also cover machine learning techniques relevant to natural language processing. In this course, students will gain a thorough introduction to cutting-edge research in deep learning for NLP. Through lectures, assignments and a final project, students will learn the necessary skills to design, implement and understand their own neural network models.
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