What is Deep Learning and how is it different from Machine Learning?

Deep Learning is a subset of Machine Learning that uses multi-layer neural networks to automatically learn hierarchical representations from data.

Traditional Machine Learning often requires manual feature engineering, where domain experts design features before training models. Deep Learning eliminates much of this requirement by using neural networks with multiple hidden layers capable of learning low-level to high-level abstractions automatically. For example, in image processing, early layers may detect edges, middle layers detect shapes, and deeper layers identify objects. Deep Learning models are highly effective for unstructured data such as images, text, audio, and video because of their representation learning capability. However, they require larger datasets, more computational power, and longer training times compared to traditional ML algorithms.