Introduction to Topic Modelling with Bert
In Person
In this course, we will cover the basics of topic modelling and how to use Python to build, evaluate, and analyse topic models.
Topic modelling is a powerful tool for uncovering latent semantic structures in large collections of text data, providing insights into the underlying themes and trends. We will introduce you to the basics of topic modelling and discuss different approaches to data collection and ingestion. We will also cover techniques for preparing the data for analysis, including cleaning and pre-processing. We will dive into using Python for topic modelling, covering how to build and evaluate topic models using Python, as well as advanced techniques for improving the results of topic modelling. Finally, we will focus on analysing and interpreting the results of topic modelling, including visualizing the results using Python.
We will also discuss real-world applications of topic modelling and wrap up the course with a conclusion.
This is an advanced course. You will need a basic understanding of Python and how to run Python code. Previous knowledge of text analysis and NLP will also be required to follow the content of this course.
Those who have registered to take part will receive an email with full details on how to get ready for the course.
This course will be taught by Xan Cochran.
After taking part in this event, you may decide that you need some further help in applying what you have learnt to your research. If so, you can book a Data Surgery meeting with one of our training fellows.
More details about Data Surgeries.
If you’re new to this training event format, or to CDCS training events in general, read more on what to expect from CDCS training. Here you will also find details of our cancellation and no-show policy, which applies to this event.
Learning Outcomes:
Understand the basics of topic modelling.
Familiarise with the steps needed to set up unstructured datasets to perform topic modelling.
Explore what topic modelling can and cannot do when applied to real word data.
Familiarise with packages and functions in Python (LDA and BERTopic) to perform topic modelling analysis and how different approaches generate very different results.
Interpret the results of the different analyses (LDA and BERTopic).
If you're interested in other training on text analysis, have a look at the following:
Return to the Training Homepage to see other available events.
Room 4.35, Edinburgh Futures Institute
This room is on Level 4, in the North East side of the building.
When you enter via the level 2 East entrance on Middle Meadow Walk, the room will be on the 4th floor straight ahead.
When you enter via the level 2 North entrance on Lauriston Place underneath the clock tower, the room will be on the 4th floor to your left.
When you enter via the level 0 South entrance on Porters Walk (opposite Tribe Yoga), the room will be on the 4th floor to your right.
