Deep Learning

Deep learning models use neural networks containing multiple layers that progressively transform input data into increasingly complex representations. During training, these networks automatically learn useful features rather than relying entirely on manually defined ones. Architectures such as convolutional neural networks, recurrent neural networks, and transformers are commonly associated with deep learning.

Deep learning enables AI systems to process highly complex and unstructured data such as images, text, audio, and video. It has driven major advances in areas where traditional machine learning techniques may struggle, particularly when large datasets and substantial computing resources are available.