Model Types
Learn about the different types of models that are present in Deep Learning.
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Nested models
In our model, we manually created two parameters to perform a linear regression. Instead of defining individual parameters, what if we use PyTorch’s Linear model?
We are implementing a single feature linear regression, one input, and one output, so the corresponding linear model would look like this:
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import torch.nn as nnlinear = nn.Linear(1, 1)print(linear)
Do we still have our b and w parameters? Sure we do!
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import torch.nn as nnlinear = nn.Linear(1, 1)print(linear.state_dict())
So, our former parameter b is the bias, and our former parameter w is the weight. Your values will be different since random seed has not been set up ...
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