BERTopic Explained
Offered By: James Briggs via YouTube
Course Description
Overview
Explore the advanced topic modeling technique BERTopic in this comprehensive 45-minute video tutorial. Learn how transformer models, UMAP, and HDBSCAN combine to organize unstructured text data efficiently. Dive into the components of BERTopic, including transformer embedding, dimensionality reduction, clustering, and c-TF-IDF. Discover how to get started with BERTopic, customize it for specific needs, and understand its potential in processing large amounts of textual information. Gain insights into the challenges of unstructured data and how BERTopic leverages machine learning to overcome them, making text organization more accessible and meaningful in today's information age.
Syllabus
Intro
In this video
BERTopic Getting Started
BERTopic Components
Transformer Embedding
Dimensionality Reduction
UMAP
Clustering
c-TF-IDF
Custom BERTopic
Final Thoughts
Taught by
James Briggs
Related Courses
Integrate Single-Cell RNA-Seq Datasets in R Using Seurat - Detailed Seurat Workflow TutorialBioinformagician via YouTube Clustering and Markers Identification for ScRNA-Seq - Seurat Package Tutorial
LiquidBrain Bioinformatics via YouTube Dimensionality Reduction in R
DataCamp CLIP, T-SNE, and UMAP - Master Image Embeddings and Vector Analysis
Roboflow via YouTube Practical Clustering and Topological Data Analysis
Applied Algebraic Topology Network via YouTube