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Deep Learning

The Evolution of Deep Learning Frameworks: Past, Present, and Future

Deep Learning is a subfield of machine learning that focuses on teaching computers to learn from data through artificial neural networks. These artificial neural networks are inspired by the structure and function of the human brain and consist of multiple layers of interconnected nodes or neurons.

Deep learning algorithms can automatically extract features and patterns from raw data, such as images, audio, or text, without the need for explicit human intervention or manual feature engineering. This makes deep learning particularly suited for tasks involving large amounts of high-dimensional data, such as image and speech recognition, natural language processing, and playing games like Go or chess.

Deep learning models can be trained using supervised, unsupervised, or semi-supervised learning techniques, and they have been responsible for many recent advancements in artificial intelligence, including the development of state-of-the-art computer vision systems, language translation models, and reinforcement learning agents.

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