<ul><li>Dense neural networks are essential for compressing information from higher-dimensional data into structured outputs.</li><li>Hidden layers in DNNs are fully connected layers between the input and output layers.</li><li>Dense layers use activation functions to introduce non-linearities into the model, enabling it to capture complex patterns.</li><li>DNNs are commonly used for classification in structured data, regression tasks, reinforcement learning, and as final dense layers in NLP architectures.</li></ul>

Understanding Dense Neural Networks: A Deep Dive into Architecture, Learning, and Applications

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