Feed Your OWN Documents to a Local Large Language Model!
Host ALL your AI locally
New Free AI - chat.notdiamond.ai
This page is a short, curated list of YouTube videos on machine learning and applied AI that are useful as companions to the written pages on this site. Video is good for seeing a tool run end to end; the written references are better for looking up details later.
Feed Your OWN Documents to a Local Large Language Model!
Host ALL your AI locally
New Free AI - chat.notdiamond.ai
Intro to Databricks Lakehouse Platform
Build Anything with Claude MCP Agents
Run your own AI (but private)
The videos fall into four groups. Several show how to run large language models on your own hardware, which matters when data cannot leave the machine. One group shows feeding your own documents to a local model, which is retrieval-augmented generation in its simplest form. An introduction to the Databricks Lakehouse Platform covers the data side. A walkthrough of building agents with Claude and the Model Context Protocol (MCP) shows how models call external tools.
| If you want to | Watch | Then read |
|---|---|---|
| Run a model locally | Local AI videos | LLMs in Production |
| Search your own files with an LLM | Feed your own documents | Search and Retrieval |
| Understand the lakehouse | Intro to Databricks | Databricks |
| Build tool-using agents | Claude MCP agents | LLM Engineering |
Tooling in this area changes quickly, so treat any video as a snapshot: check the publication date, and compare commands and version numbers against the current project documentation before copying them. Product names and free tiers shown in older videos may no longer exist.
A good way to get value from a demo video is to reproduce it rather than only watch it. Pause after each step, run the same commands on your own machine with a small sample of your own data, and note where your result differs. Differences usually point to a version change, a missing dependency, or an assumption the presenter did not state, and working through them teaches more than the video itself. Keep short notes alongside each video so the useful parts are easy to find again later.