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+#Neural Networks in CS
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+The human brain processes information, learns, and makes decisions using billions of interconnected neurons. Inspired by this, artificial neural networks (ANNs) use artificial neurons to solve tasks like recognizing speech or diagnosing medical conditions.
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+Biological and artificial NNs share a similar structure. In ANNs, the input layer receives raw information (e.g., images or text), similar to how dendrites receive information in biological networks. Each input is assigned a weight to reflect its importance.
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+The hidden layer(s) process and refine this information by analyzing patterns, mimicking how biological neurons handle inputs. The output layer makes the final decision, such as identifying an object or answering a question, analogous to the axon in biological neurons.
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+Training adjusts the weights to improve the network’s performance, enabling it to learn from data and become increasingly accurate, much like how the brain improves with practice.
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+##Miroslava Macejkova