Dataset: Training, Validation and Test

This lecture provides a gentle introduction to machine learning, focusing on the initial steps when starting a machine learning problem, typical problems like classification and regression, and how to solve them. The instructor explains the importance of dividing the dataset into training, validation, and test subsets, with the training subset usually being 50%, validation 20%, and the test set 30% of the database. It emphasizes the need to keep the test set secure and untouched until the final stage, using the training and validation sets to build and refine the model.