Neural Network Evolution
The discovery of multilayer networks in the eighties revolutionized learning algorithms, particularly with the rise of backpropagation, which efficiently minimizes error through stochastic gradient descent. As neural networks evolve, they are now tackling increasingly complex problems with architectures that boast over 200 layers, showcasing their remarkable scalability and parallel processing capabilities.In this clip
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