After the installation was successfully completed, I recommend creating a new virtual environment called `dl-fundamentals`, which you can do by executing
> Many scientific computing libraries do not immediately support the newest version of Python. Therefore, when installing PyTorch, it's advisable to use a version of Python that is one or two releases older. For instance, if the latest version of Python is 3.13, using Python 3.10 or 3.11 is recommended.
If you want to style your terminal similar to mine so that you can see which virtual environment is active, check out the [Oh My Zsh](https://github.com/ohmyzsh/ohmyzsh) project.
To install new Python libraries, you can now use the `conda` package installer. For example, you can install [JupyterLab](https://jupyter.org/install) and [watermark](https://github.com/rasbt/watermark) as follows:
PyTorch can be installed just like any other Python library or package using pip. For example:
```bash
pip install torch==2.0.1
```
However, since PyTorch is a comprehensive library featuring CPU- and GPU-compatible codes, the installation may require additional settings and explanation (see the *A.1.3 Installing PyTorch in the book for more information*).
It's also highly recommended to consult the installation guide menu on the official PyTorch website at [https://pytorch.org](https://pytorch.org).