Deep Learning · TEE · section

MT1B Q1b

Current MT1 and the two teacher backprop examples

Question

Question (2 marks). Differentiate machine learning and deep learning with respect to feature extraction and data requirements.

Answer — step by step

Traditional machine-learning pipelines often rely on manually selected or engineered features; deep networks often learn feature representations jointly with the task. Training a large deep network from scratch commonly needs more data than simpler models. However, pretrained deep features can be useful even with a small target dataset. These are practical tendencies, not absolute definitions.