## The PyTorch Softmax Function

Posted 2021-01-29 • Last updated 2021-10-14You can use the top-level torch.softmax() function from PyTorch for your softmax activation needs.

You can use the top-level torch.softmax() function from PyTorch for your softmax activation needs.

When you absolutely have to iterate over rows in a Pandas DataFrame, use the .itertuples() method.

This post describes a trick for installing/upgrading Python packages in a Jupyter notebook. It’s useful for scratch code, but don’t do this when you need reproducible code.

The histplot() function in Seaborn is a great API for plotting histograms to visualize the distribution of your Pandas columns.

You can use the torchvision Normalize() transform to subtract the mean and divide by the standard deviation for image tensors in PyTorch. But it’s important to understand how the transform works and how to reverse it.

There are a few ways to drop columns and rows in Pandas. This post describes the easiest way to do it and provides a few alternatives that can sometimes be useful.

Two easy recipes for renaming column(s) in a Pandas DataFrame.

This post explains how the NumPy reshape operation works, how to use it and gotchas to watch out for.

You can calculate the L1 and L2 norms of a vector or the Frobenius norm of a matrix in NumPy with np.linalg.norm(). This post explains the API and gives a few concrete usage examples.

Using and suppressing scientific notation in Python and NumPy.

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