# Algorithms Visualized

> A free, dependency-free educational web application with 40 interactive algorithm visualizations, adjustable parameters, step-by-step explanations, and from-scratch Python examples.

Canonical URL: https://algorithms.lolisoft.eu/
Language: English
License: MIT

## Learning paths

- [Machine Learning](https://algorithms.lolisoft.eu/#ml): 20 lessons spanning regression, classification, clustering, dimensionality reduction, anomaly detection, neural-network training, and reinforcement learning.
- [LLM Algorithms](https://algorithms.lolisoft.eu/#llm): 10 lessons covering tokenization, embeddings, positional signals, attention, transformer blocks, KV caching, sampling, and beam search.
- [Sorting Algorithms](https://algorithms.lolisoft.eu/#sorting): 10 classic algorithms visualized using their real comparison, swap, write, partition, heap, digit, and bucket traces.

## Important resources

- [Interactive application](https://algorithms.lolisoft.eu/)
- [Algorithm documentation](https://algorithms.lolisoft.eu/docs/): Comprehensive guides for all 40 algorithms with formulas, from-scratch Python, practical library tutorials, evaluation advice, pitfalls, and official references.
- [Source repository](https://github.com/jomardyan/ml-algorithms-visualized)
- [Project documentation](https://github.com/jomardyan/ml-algorithms-visualized#readme)
- [XML sitemap](https://algorithms.lolisoft.eu/sitemap.xml)

## Usage notes

The visualizations use deterministic synthetic examples to teach each central mechanism. Every guide separates its educational, dependency-light implementation from a practical workflow using an established library and links to that library's official documentation.