Training ML Model with Smallest Dataset

Could you share your experiences working with small datasets to train machine learning models? What was the smallest dataset you worked with, and how did you approach model selection, training data selection, feature engineering, and validation? What challenges did you encounter, and what strategies did you employ to overcome them?