deep-learning
Mean squared error
taught
Taught in
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Fitting a line by eye
Deep Learning / Neural Networks
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Mean squared error
Deep Learning / Neural Networks
Requires
- error-and-squared-error required
Required by
- Fitting a line with gradient descent required
- Huber loss required
- Minibatch SGD for linear regression required
- Scatter points and an overlaid fitted line required
- The Gaussian-noise / squared-loss connection required
- nn.MSELoss, nn.BCELoss, and nn.CrossEntropyLoss required
Local knowledge map
Local knowledge map
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Solid arrows are required prerequisites; dashed are recommended or helpful. Lower rows are more foundational. Click any box to jump to that concept.