Build your personal knowledge base with Trilium Notes

TidGi is an privatcy-in-mind, automated, auto-git-backup, freely-deployed Tiddlywiki knowledge management Desktop note app, with local REST API. 「 太记 」是一个基于「 太微 TiddlyWiki 」的知识管理桌面应用，能保护隐私内容、高级自动化、自动Git云备份、部署为博客，且可通过RESTAPI与Anki等应用连接。（迭代开发中欢迎试用，开发进度见下方链接）(Under active development, see website below for details)

Piggydb is a Web notebook application that provides you with a platform to build your knowledge personally or collaboratively.

AI 应用示例合集

Active WIP for experimenting with GraphRAG and Knowledge Graphs

Example notebooks that illustrate how to generate knowledge-based features. Features can be used in a variety of ML models, including recommender systems.

Zettelkasten notebook utility

This repository contains a series of 4 jupyter notebooks demonstrating how AWS AI Services like Amazon Rekognition, Amazon Transcribe and Amazon Comprehend can help you extract valuable metadata from your video assets and store that information in a Graph database like Amazon Neptune for maximum query performance and flexibility.

A notebook example illustrating Graphyp

FAIR Jupyter: a knowledge graph for semantic sharing and granular exploration of a computational notebook reproducibility dataset.

This repository contains notebooks for building knowledge graphs and using them to improve Retrieval Augmented Generation (RAG) systems. RAG leverages knowledge graphs with embedding models to enhance the quality of text retrieved for language models.

This repo offers a workflow dedicated to utilizing BERTopic for Semantic Graph-based information retrieval in nutrigenomics. It includes Jupyter notebooks on topic modeling and semantic graph creation, aimed at enhance genetic literature exploration. Ideal for genomic researchers, it simplifies the analysis of nutrition-related genetic information.

Project Portfolio Frameworks. Set-up for a framework for a particular sector/company. Extract and modify from existing frameworks. Or apply Natural Language Processing to your current project documents to find the structure of your particular business domain. Do this by running simple code laid out in Notebook format.