Neural Networks and Deep Learning
Neural networks are a subset of machine learning, inspired by the structure and function of the human brain. They consist of interconnected layers of "neurons" or nodes, each processing information and passing it to the next layer. Deep learning refers to neural networks with many layers (hence "deep"), which allows them to learn incredibly complex patterns from vast amounts of data.
This is the technology behind many of today's most impressive AI achievements, including image recognition, natural language translation, and sophisticated game-playing AI. By training on massive datasets, these models can learn hierarchical features—from simple edges and colors in an image to complex concepts like "cat" or "dog"—without being explicitly programmed. The field is rapidly evolving, with new architectures and techniques continually pushing the boundaries of what machines can learn and do.
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