What is a step?
A forward pass and backward pass of one batch.
step explained in plain English
A forward pass and backward pass of one batch. See backpropagation for more information on the forward pass and backward pass.
Example
Practitioners refer to step when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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A function that enables neural networks to learn nonlinear (complex) relationships between features and the label.
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A sophisticated gradient descent algorithm that rescales the gradients of each parameter, effectively giving each parameter an independent learning rate.
- Attention
A mechanism that lets a model focus on the most relevant parts of its input when producing an output, weighting what matters most in context.
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A model that infers a prediction based on its own previous predictions.
- autoencoder
A system that learns to extract the most important information from the input.
- auxiliary loss
A loss function—used in conjunction with a neural network model's main loss function—that helps accelerate training during the early iterations when weights are randomly initialized.
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The process that tells a neural network which internal settings caused an error and how to adjust them, working backwards through layers.
- batch
The set of examples used in one training iteration.
- batch normalization
Normalizing the input or output of the activation functions in a hidden layer.