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Deep learning involves training deep neural networks for complex tasks from "summary" of Machine Learning by Stephen Marsland
Deep learning is a powerful approach to machine learning that revolves around training deep neural networks to perform complex tasks. These tasks can range from image and speech recognition to natural language processing and autonomous driving. The key idea behind deep learning is to use multiple layers of interconnected neurons to learn hierarchical representations of data. By learning more abstract and complex features at each layer, deep neural networks can model intricate patterns and relationships in the data. Training deep neural networks involves feeding them large amounts of labeled data to learn from. The network adjusts its internal parameters through a process called backpropagation, where the error between the predicted output and the true output is propagated back through the network to update the weights. This iterative process continues until the network reaches a satisfactory level of performance on the task at hand. Deep learning algorithms, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), have been instrumental in driving advancements in various fields, including co...
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