Deep learning

Deep learning is an artificial intelligence (AI) approach to machine learning that allows computers to learn to identify patterns without being explicitly programmed. It is a subfield of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. The neural network is designed to recognize features and patterns within a dataset so it can eventually classify data automatically. Deep learning has been used for many tasks, such as image recognition, voice recognition, and language translation.

Deep learning takes inspiration from the functioning of neurons in the human brain. It uses layers of artificial neurons that are organized in a hierarchy to identify patterns in data. Each layer reveals progressively more complex features, allowing the computer to learn more complex concepts. The layers further down can also learn from the layers that are higher up.

Deep learning is capable of analyzing large amounts of data and processing the data quickly and efficiently. It can also learn from unstructured data, such as images and audio recordings, and can pick out patterns that it cannot find in structured data. This makes deep learning especially useful in fields like computer vision, speech recognition, natural language processing, and robotics.

Deep learning systems are increasingly being used to power services and products in many industries, including healthcare, telecommunications, video games, and retail. They are employed for tasks such as sentiment analysis, object detection, and product recommendations. The use of deep learning is only likely to increase as companies seek better ways to utilize available data.