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Dictionary of Applied Machine Learning

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Look up, search and cross-reference machine-learning terms from dictionaryofml.org.

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Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http dictionary-of-applied-machine-learning 'https://dictionaryofml.org/mcp'
Configuration JSON (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "dictionary-of-applied-machine-learning": {
            "type": "http",
            "url": "https://dictionaryofml.org/mcp"
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Dictionary of Applied Machine Learning — companion repository
  2. Provenance and disclaimer
  3. MCP server
  4. Citing
  5. License

Dictionary of Applied Machine Learning — companion repository

Companion code for the Dictionary of Applied Machine Learning (course edition, CC BY 4.0): 107 machine-learning terms, each defined precisely and cross-referenced, with citations, a typeset PDF, and a Python demo that recomputes what the entry states.

DirectoryContents
notebooks/The per-term Python demos as Jupyter notebooks — each opens in Colab with one click from its demo page
mldict/mldict.sty: the dictionary's notation as a LaTeX package (\usepackage{mldict})
mcp/An MCP server exposing the dictionary to AI assistants (Claude Code, VS Code Copilot, …)

The notebooks and mldict.sty are generated from the dictionary's source; edits belong there, not here. The dictionary itself — definitions, symbol list, per-term PDFs — lives at dictionaryofml.org; the full content is also machine-readable as terms.json and indexed for LLM crawlers in llms.txt.

Provenance and disclaimer

The source code in this repository (demo notebooks, LaTeX package, MCP server) was created with the help of large language models (LLMs), under review by the author. It is provided as is, without warranty of any kind: use at your own risk and verify results independently before relying on them.

Basic checks are applied to the Python demos before release:

  • each demo runs its own check() assertions on the quantities it computes, with fixed random seeds for reproducibility;
  • ruff check --select F (correctness rules only: undefined and unused names);
  • bandit, restricted to the exec/eval/shell-injection checks (B102, B307, B602, B605) — the one deliberate exception is the llm demo, whose subject is an LLM wrapper executing emitted code;
  • project-specific linters for figure style and for keeping a demo's prose within the concepts its dictionary entry introduces.

These are screens, not proofs of correctness.

The demos import two third-party packages, numpy and matplotlib (both preinstalled on Colab); the source repository pins their exact versions, since the committed figure data is byte-reproducible only under the pinned pair.

MCP server

pip install -r mcp/requirements.txt
claude mcp add --scope user dictionaryofml -- python /path/to/mcp/server.py

Tools: list_all_terms, lookup_term, search_terms, get_related_terms. Content is fetched from the site's terms.json and cached for a day.

Citing

@misc{dictml,
  author = {Jung, Alexander and Olioumtsevits, Konstantina and Schnoor, Ekkehard},
  title = {Dictionary of Applied Machine Learning (course edition)},
  doi = {10.5281/zenodo.21569296},
  note = {ISBN 978-952-64-3013-3, CC BY 4.0},
  url = {https://dictionaryofml.org}
}

Each term page carries its own "Cite this entry" BibTeX block. This repository is a course-edition companion, distinct from the copyrighted Springer Dictionary of Applied Machine Learning.

License

CC BY 4.0. Maintained by Alexander Jung, Aalto University; corrections and suggestions are welcome at the address on dictionaryofml.org.

Questions fréquentes

Qu'est-ce que Dictionary of Applied Machine Learning ?

Look up, search and cross-reference machine-learning terms from dictionaryofml.org.

Comment installer Dictionary of Applied Machine Learning ?

Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http dictionary-of-applied-machine-learning 'https://dictionaryofml.org/mcp'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour Dictionary of Applied Machine Learning ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

Dictionary of Applied Machine Learning est-il open source ?

Son code est public sur GitHub, mais le dépôt ne déclare pas de licence standard.

Qui maintient Dictionary of Applied Machine Learning ?

Il est publié par alexjungaalto. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.