Technical Workshop Series
Python Programming for Topic Modeling: NLP Techniques for Data Analysis and Insights (2nd Offering)
Presenter: Soroush Ziaeinejad
Date: Tuesday, June 11th, 2024
Time: 2:00 pm
Location: 4th Floor (Lecture Space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
This is a hands-on workshop; please bring your laptop.
Abstract: In this hands-on workshop, you will gain practical experience in Python programming for NLP tasks, focusing on topic modelling. In addition to topic modelling, you will learn other advanced NLP techniques for data analysis and insights, including sentiment analysis, named entity recognition, and text classification. Through a series of guided coding exercises, you will gain experience implementing these techniques using popular Python libraries such as NLTK, genism, and sci-kit-learn.
Workshop Outline: By the end of the workshop, you will have a deeper understanding of how to leverage topic modelling to extract meaningful insights from unstructured text data and the hands-on experience to apply these techniques to your projects.
Introduction
- What is topic modelling, and how can it be used to analyze unstructured text data?
Programming
- How can text data be preprocessed for topic modelling?
- How are topic models built using popular Python libraries?
- How is the performance of a topic model evaluated?
- How do you select the appropriate NLP technique for specific data analysis needs?
- How can the skills learned in this workshop be applied to your projects and research?
Prerequisites:
Basic knowledge of NLP, Python, and mathematics
Biography:
Soroush is a Ph.D. student and research assistant at the School of Computer Science. His main research area is Natural Language Processing and Information Retrieval on social networks.