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Fundamentals of Deep Learning, Back Propagation. Backpropagation, a fundamental deep learning algorithm central to training neural networks, was popularized in the 1980s but has roots tracing back earlier Paul Werbos is credited with formalizing backpropagation in his 1974 PhD thesis, providing a systematic way to compute gradients efficiently in multi layer networks Despite its potential, pioneers in the AI space such as Marvin Minsky were initially skeptical, hesitating to use backpropagation
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