Data requirements vary based on factors like project complexity, task type, and algorithms. Generally, more data enhances outcomes. Basic tasks like image filtering may need less data. Yet, for advanced tasks like object detection or deep learning-based image classification, a larger dataset is vital for accuracy. Typically, hundreds to thousands of labeled images serve as a solid starting point for training machine learning models. Ideal dataset size is determined through experimentation and aligning with project goals.