Natural Language Processing and Recommender Systems
|Lecture hours per week||2|
|Lab hours per week||2|
The first part of this course focuses on natural language procession concepts and techniques. Topics include sentiment analysis, summarization, dialogue state tracking, etc. Students will apply these concepts to build a conversational interface (chat bot).
The second part of the course introduces recommender systems for predicting user preferences. Topics include the most fundamental techniques used in recommender systems, such as association rules and collaborative filtering. More advanced techniques will be also explained.