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Deep Learning

Deep Learning Models: Bridging the Gap Between Human and Artificial Intelligence

Deep learning is a subfield of artificial intelligence (AI) and machine learning that focuses on using artificial neural networks to model and solve complex problems. These neural networks are inspired by the architecture and functioning of the human brain, particularly the way neurons process and transmit information.

Deep learning techniques have been used to achieve significant advancements in various domains such as computer vision, natural language processing, speech recognition, and game playing. The “deep” in deep learning refers to the depth of the neural networks, which can consist of multiple layers of interconnected nodes or neurons. As data passes through these layers, the network can automatically learn hierarchical representations and increasingly abstract features from the input data.

Deep learning has gained immense popularity due to its ability to process large amounts of unstructured data, such as images, text, and audio, and its capacity to learn from this data without explicit human intervention or programming. Some popular deep learning frameworks include TensorFlow, Keras, and PyTorch.

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