I feel we should follow Pytorch to add equations to APIs --- for example, https://pytorch.org/docs/stable/nn.html#torch.nn.Conv1d. I personally believe that is how a math library's documentation should look like. Also, debugging ML models is quite different from debugging typical code --- debugging ML model (such as figuring why it doesn't work) requires knowledge of the underlying mathematical models.
I feel we should follow Pytorch to add equations to APIs --- for example, https://pytorch.org/docs/stable/nn.html#torch.nn.Conv1d. I personally believe that is how a math library's documentation should look like. Also, debugging ML models is quite different from debugging typical code --- debugging ML model (such as figuring why it doesn't work) requires knowledge of the underlying mathematical models.