https://github.com/glemaitre/sacl-ai-2024

https://github.com/glemaitre/sacl-ai-2024

Last synced: 8 days ago
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• Host: GitHub
• URL: https://github.com/glemaitre/sacl-ai-2024
• Owner: glemaitre
• License: cc0-1.0
• Created: 2024-07-04T08:02:18.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-07-08T10:03:00.000Z (6 months ago)
• Last Synced: 2024-10-28T07:54:46.624Z (about 2 months ago)
• Language: Jupyter Notebook
• Size: 1 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Sacl-AI 2024

## Structure of the repository

A pure python file with `jupytext` markers are available in `python_files` directory.

We converted these files to `ipynb` files using `jupytext` and saved them in the

`notebooks` directory.

Similarly, we provide the corrections of the python files and notebooks in the

`python_files_corrections` and `notebooks_corrections` directories respectively.

## Getting started

### Using Google Colab

You can open any of the notebooks in Google Colab: https://colab.research.google.com/

Once the notebook imported, you will need to install/update two libraries using the

following commands:

```bash

!pip install -q -U scikit-learn skrub

```

Another change to be done in the notebook is to replace the link to the data file

and provide the URI of the data from the GitHub repository.

Basically, the changes are:

Replace `../datasets/penguins_regression.csv` with the following URI:

`https://raw.githubusercontent.com/tomMoral/24-sacl-ai-4-sciences/main/session-2/datasets/penguins_regression.csv`

Replace `../datasets/penguins.csv` with the following URI:

`https://raw.githubusercontent.com/tomMoral/24-sacl-ai-4-sciences/main/session-2/datasets/penguins.csv`

### Using `pixi`

An easy way to get started is to use `pixi` for the environment management.

Alternatively, you can use `conda` or `pip` to install the required packages as shown

in the sections below. Refer to [following link](https://pixi.sh/latest/#installation)

for installing `pixi`.

Once `pixi` installed, you just start `jupyterlab`:

```bash

pixi run jupyter lab

```

### Using `conda`

Alternatively you can create a new conda environment which will be called

`sacl-ai` by default and will contain all the packages required to run the

notebooks:

``` bash

conda env create -f environment.yml

```

```bash

conda activate sacl-ai

jupyter notebook  # or jupyter lab

```

You can also update an existing `conda` environment:

``` bash

conda env update -f environment.yml

```

### Using `pip`

We provide a `requirements.txt` file that you can use to install the required

packages using `pip`:

```bash

pip install -r requirements.txt

jupyter notebook  # or jupyter lab

```