tutorials

NePS Tutorials

Interactive tutorials for learning hyperparameter optimization and neural architecture search with NePS.

Tutorials

Tutorial	Description	Run
1. Getting Started with HPO	Basic HPO workflow, synthetic functions, and deep learning tasks	Local · Colab
2. Defining Search Spaces	Parameter types, fidelity parameters, and PipelineSpace classes	Local · Colab
3. Efficient Optimization	Multi-fidelity optimization, expert priors, and advanced strategies	Local · Colab
4. Multi-Objective Optimization	Multi-objective optimization with PriMO, including per-objective expert priors	Local · Colab

Quick Start

Run in Google Colab (Recommended)

Click the Colab link in the table above. No setup required.

Run Locally

Install dependencies:

pip install -r requirements.txt

Run a tutorial:

python 1_getting_started_hpo.py

Or use Jupyter:

pip install jupytext
jupytext --to notebook 1_getting_started_hpo.py
jupyter notebook 1_getting_started_hpo.ipynb

Resources

• Documentation
• GitHub Repository
• API Reference
• More Examples