AI & Machine Learning
AI Tools and Machine Learning
An honest status page: the AI and machine learning ground Codertronix covers today, and the guides that are not written yet.
An honest status page: the AI and machine learning ground Codertronix covers today, and the guides that are not written yet.
Where AI and machine learning actually appear in these tutorials
Natural language processing with spaCy: tokenisation, named entity recognition and building a text pipeline that survives real input. Read the tutorial.
A model is only as good as what you feed it. Pandas for data analysis and PostgreSQL query optimisation cover the cleaning and querying that comes first.
Once something works locally it needs an endpoint. FastAPI and GraphQL with Apollo Server cover both styles.
Not written yet. There are no tutorials here on ChatGPT, GitHub Copilot, Claude, Cursor or prompt engineering. They are on the list, and this page will link to them once they exist rather than before. If a topic is not linked above, assume it is not covered.
The data, API and infrastructure groundwork that AI and ML projects depend on
AI tooling moves quickly, and guides to the assistants above are planned rather than published. Rather than list them as if they were ready, this page will add each one when it is actually written and tested. The RSS feed carries every new tutorial, so that is the reliable place to watch.