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+---
+Title: '.log10()'
+Description: 'Returns a tensor containing the base-10 logarithm of each element in the input tensor.'
+Subjects:
+  - 'Computer Science'
+  - 'Machine Learning'
+Tags:
+  - 'Functions'
+  - 'Machine Learning'
+  - 'Python'
+  - 'Tensor'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/computer-science'
+---
+
+In PyTorch, the **`.log10()`** function computes the base-10 logarithm of each element in the input [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors). Mathematically, this is equivalent to applying the function $y_i = \log_{10}(x_i)$ element-wise, where $log_{10}$ is the base-10 logarithm.
+
+## Syntax
+
+```pseudo
+torch.log10(input, *, out=None) → Tensor
+```
+
+**Parameters:**
+
+- `input`: The input tensor containing elements for which the logarithm will be computed.
+- `out` (optional): A tensor to store the output. If provided, the result is written to this tensor. Must have the same shape as `input`.
+
+**Return value:**
+
+Returns a new tensor where each element is the base-10 logarithm of the corresponding element in `input`.
+
+## Example
+
+The following example shows how to compute the element-wise logarithm base 10 of a tensor using `torch.log10()`:
+
+```py
+import torch
+import math
+
+# Define a tensor
+x = torch.tensor([5.0 , 6.0 , 7.0 , math.log(2.) ])
+
+# Compute the logarithm base 10
+result = torch.log10(x)
+
+print(result)
+```
+
+Here is the output:
+
+```shell
+tensor([ 0.6990,  0.7782,  0.8451, -0.1592])
+```