Feat: [Term Entry] PyTorch Tensor Operations .select() (#5783)

* [Term Entry] PyTorch Tensor Operations .select()

* Fix Linting Issues

* Update select.md

minor fixes

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

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+---
+Title: '.select()'
+Description: 'Selects a specific slice along the given dimension in a tensor.'
+Subjects:
+  - 'Computer Science'
+  - 'Machine Learning'
+Tags:
+  - 'Functions'
+  - 'Machine Learning'
+  - 'Methods'
+  - 'Python'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/computer-science'
+---
+
+The **`.select()`** method in PyTorch returns a specific slice of a [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors) along a specified dimension, reducing the dimensionality of the output tensor by one compared to the input tensor.
+
+## Syntax
+
+```pseudo
+torch.select(input, dim, index)
+```
+
+- `input`: The input tensor.
+- `dim`: The dimension along which to select.
+- `index`: The index of the slice to select along the specified dimension.
+
+## Example
+
+The following example illustrates the usage of `.select()` method:
+
+```py
+import torch
+
+# 2D tensor
+tensor = torch.tensor([[10, 20], [30, 40], [50, 60]])
+print("Input Tensor: ", tensor)
+
+# Select a row (dim=0)
+row = torch.select(tensor, 0, 1)
+print("\nSelected Row (dim=0, index=1):", row)
+
+# Select a column (dim=1)
+col = torch.select(tensor, 1, 0)
+print("\nSelected Column (dim=1, index=0):", col)
+```
+
+The above code gives the following output:
+
+```shell
+Input Tensor:  tensor([[10, 20],
+        [30, 40],
+        [50, 60]])
+
+Selected Row (dim=0, index=1): tensor([30, 40])
+
+Selected Column (dim=1, index=0): tensor([10, 30, 50])
+```