A neural network is a type of machine learning algorithm modeled after the human brain. It is composed of interconnected nodes called neurons, which are used to process and store information. Neural networks are used in a variety of applications, such as image recognition, natural language processing, and autonomous vehicles.
Deep learning is a subset of machine learning that uses artificial neural networks with many layers of processing units to learn from large amounts of data. It is used for a variety of tasks such as computer vision, natural language processing, and voice recognition. Deep learning networks can learn to identify patterns and features from raw data, making them more accurate and efficient than traditional machine learning algorithms.
For example, a neural network might be used to identify objects in an image, while a deep learning network could be used to identify objects in a video. In both cases, the networks are trained to recognize patterns and features in the data, but the deep learning network is able to capture more complex patterns due to its multiple layers of processing units.