Popular GitHub Repositories for Health Questions

AI's query engine - Platform for building AI that can learn and answer questions over large scale federated data.

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

A one stop repository for generative AI research updates, interview resources, notebooks and much more!

Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.

High accuracy RAG for answering questions from scientific documents with citations

OpenHealth, AI Health Assistant | Powered by Your Data

Mirix is a multi-agent personal assistant designed to track on-screen activities and answer user questions intelligently. By capturing real-time visual data and consolidating it into structured memories, Mirix transforms raw inputs into a rich knowledge base that adapts to your digital experiences.

Datawhale成员整理的面经，内容包括机器学习，CV，NLP，推荐，开发等，欢迎大家star

AIGC-interview/CV-interview/LLMs-interview面试问题与答案集合仓，同时包含工作和科研过程中的新想法、新问题、新资源与新项目

AI算法工程师面试宝典：三年面试经验，五年模拟题库！本书涵盖AIGC、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、强化学习、具身智能、元宇宙、AGI等人工智能领域的面试笔试真题及实用技巧，助你轻松应对AI行业挑战。

记录cv算法工程师的成长之路，分享计算机视觉和模型压缩部署技术栈笔记。https://harleyszhang.github.io/cv_note/

Query your Apple Health data with natural language ? ?

SparkyFitness: Built for Families. Powered by AI. Track food, fitness, water, and health — together.

心理健康大模型、LLM、The Big Model of Mental Health、Finetune、InternLM2、InternLM2.5、Qwen、ChatGLM、Baichuan、DeepSeek、Mixtral、LLama3、GLM4、Qwen2、LLama3.1

This repository contains the code for "Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference"

【三年面试五年模拟】AI算法工程师面试秘籍。涵盖AIGC、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、强化学习、具身智能、元宇宙、AGI等AI行业面试笔试经验与干货知识。

LLMs interview notes and answers:该仓库主要记录大模型（LLMs）算法工程师相关的面试题和参考答案

This Repositry is an experiment with an agent that searches documents and asks questions repeatedly in response to the main question. It automatically determines the optimal answer from the current documents or recognizes when there is no answer.

ChatWeb can crawl web pages, read PDF, DOCX, TXT, and extract the main content, then answer your questions based on the content, or summarize the key points.

Chat and Ask on your own data. Accelerator to quickly upload your own enterprise data and use OpenAI services to chat to that uploaded data and ask questions