Efficient Labelling of Large Datasets for NLP Tasks

Efficient Labelling of Large Datasets for NLP Tasks

Explore efficient techniques for labeling large datasets in Natural Language Processing tasks in this 29-minute conference talk by Nichola Roberts at the Data Science Festival. Learn how to grow a comprehensive labeled dataset from a small initial set of examples, automating the process as much as possible. Discover various methods, including traditional approaches like Support Vector Machines and cutting-edge techniques such as few-shot and zero-shot learning. Gain insights into overcoming the challenge of creating high-quality labeled datasets for NLP projects, essential for most data scientists in the field.