https://github.com/arbox/embedings-course
https://github.com/arbox/embedings-course
Last synced: 4 days ago
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- Host: GitHub
- URL: https://github.com/arbox/embedings-course
- Owner: arbox
- Created: 2026-06-22T10:10:26.000Z (12 days ago)
- Default Branch: main
- Last Pushed: 2026-06-22T10:17:53.000Z (12 days ago)
- Last Synced: 2026-06-22T12:14:27.674Z (12 days ago)
- Size: 1.95 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Embeddings Course
A short, hands-on course on numeric representations for linguistic units (word embeddings) — from the basics of vector representations to practical alignment and similarity techniques.
## What you'll learn
- How words and other linguistic units get represented as vectors
- How to train, load, and inspect embedding models
- How to measure similarity and explore embedding spaces
- Practical applications and common pitfalls
## Prerequisites
You'll need a working Python environment capable of running Jupyter notebooks, with permission to install additional packages as needed.
- **Python**: 3.10+ recommended
- **Jupyter**: JupyterLab or Jupyter Notebook installed and working
- **Package manager**: `pip`, [`uv`](https://github.com/astral-sh/uv) (or `conda`/`mamba`), with the ability to install new packages during the course
- **Admin/install rights**: you should be able to install Python packages (and, if needed, command-line tools) on your machine without IT restrictions blocking you
- **Operating system**: any *unix-like OS (macOS, Linux) is recommended; Windows works too (e.g. via WSL)
### Quick setup check
Before the course starts, please confirm you can do the following:
```bash
python3 --version # should be 3.10 or newer
pip install --upgrade pip
jupyter --version # should print without error
```
If `jupyter` isn't found, install it with:
```bash
pip install jupyterlab
# or, with uv:
uv pip install jupyterlab
```
We'll install course-specific packages (e.g. `numpy`, `gensim`, `scikit-learn`, embedding libraries) together at the start of the course.
## Getting started
1. Clone this repository
2. Set up your Python environment (see Prerequisites above)
3. Launch Jupyter and open the first notebook
```bash
git clone
cd embeddings-course
jupyter lab
```
## License
TBD