Ontology for the description of human clinical features

FastAPI Best Practices and Conventions we used at our startup

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

The Programmable Cypher-based Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected

Embeddable property graph database management system built for query speed and scalability. Implements Cypher.

Repository for all ArangoDB interactive tutorial notebooks.

PromptLink: Leveraging Large Language Models for Cross-Source Biomedical Concept Linking

Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks.

Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets

A tool to animate Excalidraw drawings

Merge Transformers language models by use of gradient parameters.

Tools for merging pretrained large language models.

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

This repository contains the discussions related to the KGC Book Club on the book Knowledge Graphs Applied

Jupyter notebooks for testing ML models

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

examples of use of the neosemantics plugin

A collection of research papers and software related to explainability in graph machine learning.

Python package for graph neural networks in chemistry and biology

A knowledge graph and a set of tools for drug repurposing

PhD Thesis

CLEVR graph: A dataset for graph based reasoning

A curated list of network embedding techniques.

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.