mélytanulási

Mélytanulási, often translated as deep learning, is a subfield of machine learning that focuses on algorithms inspired by the structure and function of the brain, specifically artificial neural networks. These networks consist of multiple layers of interconnected nodes, or neurons, which process information. The "deep" in deep learning refers to the significant number of these layers, allowing the models to learn complex patterns and hierarchical representations of data.

Unlike traditional machine learning techniques that often require manual feature engineering, deep learning models can automatically learn relevant features from raw data. This capability makes them particularly effective for tasks involving unstructured data such as images, audio, and text. For example, in image recognition, early layers of a deep neural network might detect simple edges and corners, while deeper layers combine these to recognize more complex shapes and eventually entire objects.

The training of deep learning models typically involves large datasets and substantial computational resources, often utilizing specialized hardware like Graphics Processing Units (GPUs). Backpropagation is a common algorithm used to adjust the weights of the connections between neurons to minimize errors and improve the model's performance. Deep learning has led to significant advancements in various fields, including natural language processing, computer vision, speech recognition, and recommendation systems.