Diverse Datasets for Model Training

This chapter explores the significance of utilizing a variety of datasets, including traditional annotations, synthetic data, and real-world captures, to enhance machine learning models. It discusses the benefits and challenges associated with synthetic data, its impact on model performance, and the complexities of selecting the right training sources.