Unverified50% confidenceFactExact time
The training process uses batch gradient descent for 5000 iterations.
1
Sources
50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
Building a Neural Network from Scratch with NumPy: A Hands-On Deep Dive into Backpropagation
redditr/deeplearning10/19/2026
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UnverifiedThe core process of training a model is to iteratively update parameters in the direction of the loss function's gradient via gradient descent.78% similarUnverifiedModern training frameworks use mixed-precision training and gradient scaling (loss scaling) techniques to prevent small values from being swallowed by amplifying small gradients into the representable range.71% similarUnverifiedGradient descent is the core optimization algorithm for neural network learning, and the learning rate controls the step size at each iteration.68% similarUnverified小版本号跃迁通常对应后训练（Post-Training）阶段的优化，而非预训练的重新训练65% similar
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