Navigating the Data Landscape for NLP
Akshi Kumar · 2024
This chapter delves into the complexities of data in NLP, focusing on the volume, variety, and veracity required for effective models. It covers the importance of domain-specific data, the challenges of acquiring and cleaning datasets, and the impact of data quality on NLP systems. Practical strategies for addressing data imbalances and biases are explored, emphasizing ethical considerations and the need for high-quality annotated corpora.