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BSML Official Website

Static website for the Bocconi Students for Machine Learning association, built with Jekyll.

Repository Structure

.
├── _events/       # Event markdown files
├── _hackathons/   # Hackathon descriptions
├── _layouts/      # HTML layout templates
├── _projects/     # Project pages (by date)
├── _site/         # Generated static site output
├── _theses/       # Thesis summaries and metadata
├── assets/        # CSS, JS, images, PDFs, and templates
├── pages/         # Main pages (events, hackathons, projects, theses, etc.)
├── index.html     # Homepage
└── _config.yml    # Jekyll configuration

Development

Option 1: Using Nix

Clone the repository and start a Nix development shell:

git clone https://github.com/bs-machinelearning/bs-machinelearning.github.io.git
cd bs-machinelearning.github.io
nix develop

Option 2: Using Bundler

Install dependencies and run Jekyll locally:

bundle install
bundle exec jekyll serve

Then open the site in your browser at http://localhost:4000.

Content Creation

All content (projects, events, hackathons, and theses) is managed using Markdown files for simplicity.

Each type of content lives in its own folder:

  • _projects/ → project pages
  • _events/ → event pages
  • _hackathons/ → hackathon summaries
  • _theses/ → thesis summaries and metadata

Each file uses YAML front matter to define its title, date, and other metadata. Example:

---
title: "Deep Learning for Time Series"
author: "Jane Doe"
date: 2025-05-20
tags: [deep-learning, forecasting]
---
This project explores the use of LSTM models for time-series prediction.

You can add HTML or inline CSS inside the Markdown file if you need a custom layout or visuals.

When you add a new Markdown file to one of these folders, Jekyll automatically includes it in the generated site.

Contributing

Reporting Issues

If you find a bug, missing content, or design issue, open a GitHub issue.

Opening a Pull Request

  1. Fork the repository: Click Fork on the project's GitHub page.

  2. Clone your fork:

   git clone https://github.com/<your-username>/bs-machinelearning.github.io.git
   cd bs-machinelearning.github.io
  1. Create a new branch:
   git checkout -b feature/add-new-content

  1. Make your changes (add Markdown, fix layout, etc.).

  2. Commit and push:

   git add .
   git commit -m "Add new project: Deep Learning for Time Series"
   git push origin feature/add-new-content
  1. Open a Pull Request: Go to your fork on GitHub and click New Pull Request.

Your PR will be reviewed and merged after validation.