Acosh Article Written (#6311)

* Wrote the initial article

* Rephrased a few sentences

* Minor changes

* minor fixes

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Author: SahilJoshi121

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

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+---
+Title: '.acosh()'
+Description: 'Computes the inverse hyperbolic cosine of elements in a PyTorch tensor.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Deep Learning'
+  - 'Programming'
+  - 'PyTorch'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/data-science'
+---
+
+The **`.acosh()`** method in PyTorch computes the inverse hyperbolic cosine of each element in a [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors). This operation is applied element-wise and is commonly used in scientific computations involving hyperbolic functions.
+
+## Syntax
+
+```pseudo
+torch.acosh(input, *, out=None) → Tensor
+```
+
+**Parameters:**
+
+- `input`: The input tensor containing values greater than or equal to 1.
+- `out` (Optional): The output tensor to store the result. If not provided, a new tensor is created.
+
+**Returns:**
+
+A tensor with the inverse hyperbolic cosine of each element from the input tensor.
+
+## Example
+
+This example shows how to use `.acosh()` to compute the inverse hyperbolic cosine of a tensor:
+
+```py
+import torch
+
+# Define a tensor with values >= 1
+input_tensor = torch.tensor([1.0, 2.0, 3.0, 10.0])
+
+# Compute the inverse hyperbolic cosine
+output_tensor = torch.acosh(input_tensor)
+
+print("Input Tensor:")
+print(input_tensor)
+
+print("\nOutput Tensor:")
+print(output_tensor)
+```
+
+This example results in the following output:
+
+```shell
+Input Tensor:
+tensor([ 1.,  2.,  3., 10.])
+
+Output Tensor:
+tensor([0.0000, 1.3169, 1.7627, 2.9932])
+```