Deep Learning

Executive Definition: Deep Learning — A subset of machine learning based on artificial neural networks with multiple layers that automatically learn features from raw data.

Deep learning architectures, characterized by their depth (number of hidden layers), are highly effective at discovering intricate patterns in high-dimensional data. This capability has driven major advancements in natural language processing, computer vision, and speech recognition.

Frequently Asked Questions

How is deep learning different from machine learning?

Machine learning is the overarching field. Deep learning specifically utilizes deep neural networks to learn features automatically, bypassing the need for manual feature engineering required in traditional ML.

When should I use deep learning instead of traditional ML?

Deep learning excels with unstructured data like images, audio, and text. Traditional ML is typically more efficient and interpretable for structured tabular data.

Does deep learning require a lot of data?

Generally, yes. Deep neural networks require large datasets to generalize effectively. For smaller datasets, traditional ML or transfer learning from pre-trained deep models is recommended.