[Term Entry] PyTorch Tensor Operations: .digamma()

* Create digamma entry for PyTorch

* Update digamma

* Update digamma

* Update and rename digamma to digamma.md

* Minor changes

---------

Author: arisdelacruz

content/pytorch/concepts/tensor-operations/terms/digamma/digamma.md

@@ -0,0 +1,54 @@
+---
+Title: '.digamma()'
+Description: 'Computes the digamma function, which is the logarithmic derivative of the gamma function.'
+Subjects:
+  - 'AI'
+  - 'Data Science'
+Tags:
+  - 'AI'
+  - 'Data Types'
+  - 'Deep Learning'
+  - 'Functions'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/data-science'
+---
+
+In PyTorch, the **`.digamma()`** function computes the logarithmic derivative of the gamma function, alternatively known as the digamma function. It is often used in statistical modeling, especially in variational inference and probabilistic programming.
+
+## Syntax
+
+```pseudo
+torch.digamma(input, *, out=None)
+```
+
+**Parameters:**
+
+- `input` (Tensor): The input tensor.
+- `out` (Tensor, optional): The output tensor to store results. Must be the same shape as `input`.
+
+**Return value:**
+
+Returns a tensor containing the result.
+
+## Example
+
+This example demonstrates the usage of the `.digamma()` function:
+
+```py
+import torch
+
+# Create a tensor
+x = torch.tensor([1.0, 2.0, 3.0])
+
+# Compute the digamma function
+y = x.digamma()
+
+print(y)
+```
+
+Here is the output:
+
+```shell
+tensor([-0.5772,  0.4228,  0.9228])
+```