A training dataset is a collection of data used to teach a machine learning model how to make predictions or decisions. This dataset typically includes input data and corresponding output labels, allowing the model to learn patterns and relationships. For example, in image recognition, the dataset might consist of images of animals along with labels identifying each animal. The quality and size of the training dataset significantly impact the model's performance. A larger and more diverse dataset helps the model generalize better to new, unseen data. Common sources for training datasets include public repositories, company data, and synthetic data generation techniques.