Developing a Data-Centric NLP Machine Learning Pipeline for Text Classification
MLOps World: Machine Learning in Production via YouTube
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Explore the development of a text classification pipeline for integrating with a product in this conference talk from MLOps World. Learn how to design an appropriate classification taxonomy and create a consistent annotated training dataset. Discover the process of piecing together an end-to-end pipeline to deploy a BERT-based model in a low latency real-time text classification system. Gain insights from Data Scientist Diego Castaneda and Content Strategist Jennifer Bader as they share their experience in developing a data-centric NLP machine learning pipeline, emphasizing the importance of training data in creating effective ML systems.
Syllabus
Developing a Data-Centric NLP Machine Learning Pipeline
Taught by
MLOps World: Machine Learning in Production