
Course Overview
Natural language processing (NLP) or computational linguistics is one of the most important technologies of the information age. Applications of NLP are everywhere because people communicate almost everything in language: web search, advertising, emails, customer service, language translation, virtual agents, medical reports, etc. In recent years, deep approaches have obtained very high performance across many different NLP tasks, using single end-to-end neural models that do not require traditional, task-specific feature engineering. In this course, students will gain a thorough introduction to cutting-edge research in Deep Learning for NLP.
After attending the course attendees should be able to:
• Use deep learning frameworks to define and solve various of NLP tasks.
• Read an NLP paper to keep up with future advancements.
Prerequisites
• Proficiency in Python
• Basic knowledge in Linear algebra and calculus
• Basic probability and statistics.
• Foundations of Machine Learning
Who should take this course?
Junior data scientists who wish to deepen their knowledge in Deep Learning and NLP