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Merge pull request #1603 from microsoft/simonz/format-getting-started
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Format the getting started section to make it clearer
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miguelgfierro authored Jan 10, 2022
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60 changes: 35 additions & 25 deletions README.md
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Expand Up @@ -40,41 +40,51 @@ and currently does not support version 3.8 and above. It is recommended to insta

To set up on your local machine:

To install core utilities, CPU-based algorithms, and dependencies:
* To install core utilities, CPU-based algorithms, and dependencies:

1. Ensure software required for compilation and Python libraries is installed. On Linux this can be supported by adding:
```bash
sudo apt-get install -y build-essential libpython<version>
```
where `<version>` should be `3.6` or `3.7` as appropriate.
1. Ensure software required for compilation and Python libraries
is installed.

On Windows you will need [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/).

2. Create a conda or virtual environment. See the [setup guide](SETUP.md) for more details.
+ On Linux this can be supported by adding:

3. Within the created environment, install the package from [PyPI](https://pypi.org):
```bash
sudo apt-get install -y build-essential libpython<version>
```

```bash
pip install --upgrade pip
pip install --upgrade setuptools
pip install recommenders[examples]
```
where `<version>` should be `3.6` or `3.7` as appropriate.

4. Register your (conda or virtual) environment with Jupyter:
+ On Windows you will need [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/).

```bash
python -m ipykernel install --user --name my_environment_name --display-name "Python (reco)"
```
2. Create a conda or virtual environment. See the
[setup guide](SETUP.md) for more details.

5. Start the Jupyter notebook server
3. Within the created environment, install the package from
[PyPI](https://pypi.org):

```bash
jupyter notebook
```
```bash
pip install --upgrade pip
pip install --upgrade setuptools
pip install recommenders[examples]
```

6. Run the [SAR Python CPU MovieLens](examples/00_quick_start/sar_movielens.ipynb) notebook under the `00_quick_start` folder. Make sure to change the kernel to "Python (reco)".
4. Register your (conda or virtual) environment with Jupyter:

For additional options to install the package (support for GPU, Spark etc.) see [this guide](recommenders/README.md).
```bash
python -m ipykernel install --user --name my_environment_name --display-name "Python (reco)"
```

5. Start the Jupyter notebook server

```bash
jupyter notebook
```

6. Run the [SAR Python CPU MovieLens](examples/00_quick_start/sar_movielens.ipynb)
notebook under the `00_quick_start` folder. Make sure to
change the kernel to "Python (reco)".

* For additional options to install the package (support for GPU,
Spark etc.) see [this guide](recommenders/README.md).

**NOTE** - The [Alternating Least Squares (ALS)](examples/00_quick_start/als_movielens.ipynb) notebooks require a PySpark environment to run. Please follow the steps in the [setup guide](SETUP.md#dependencies-setup) to run these notebooks in a PySpark environment. For the deep learning algorithms, it is recommended to use a GPU machine and to follow the steps in the [setup guide](SETUP.md#dependencies-setup) to set up Nvidia libraries.

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