ai
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
Neural Networks: Zero to Hero
AI app store powered by 24/7 desktop history. open source | 100% local | dev friendly | 24/7 screen, mic recording
Noise supression using deep filtering
GUI for a Vocal Remover that uses Deep Neural Networks.
12 Weeks, 24 Lessons, AI for All!
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.
Easily train a good VC model with voice data <= 10 mins!
🤖 The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transf…
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, le…
End-to-End Object Detection with Transformers
cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理
A paper list of object detection using deep learning.
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
Upload a photo of your room to generate your dream room with AI.
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
A series of large language models trained from scratch by developers @01-ai
CodeGeeX2: A More Powerful Multilingual Code Generation Model
周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！