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Backpropagation is a neural network training algorithm that helps the network learn by adjusting its weights. It calculates the error between predicted and actual outputs, then moves backward through the network to update weights proportionally. Repeating this process improves accuracy over time. It’s a fundamental method used in frameworks ...

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@howeverythingwork.s on Instagram: "In 2024, Geoffrey Hinton — a pioneer of neural networks — was awarded the Nobel Prize in Physics for foundational work that made deep learning possible. Back in the 1980s, he co-developed and popularized backpropagation, the core training method that allows neural networks to adjust weights and learn from error. That math is still powering today’s AI systems. Hinton worked at Google until 2023, then left so he could speak more openly about AI risks. In intervi

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