Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
- agent
- claude-code
- teaching
- agent-development
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Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more.
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
Tesseract Open Source OCR Engine (main repository)
计算机自学指南
Learn AI Engineering! Learn it. Build it. Ship it for others.
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
Open Data Platform for analysts, quants and AI agents.
A curated list of awesome Machine Learning frameworks, libraries and software.
:books: List of awesome university courses for learning Computer Science!
12 Weeks, 24 Lessons, AI for All!
韩先凯的人生进阶指南 AI时代 中英双语终身学习指南:AI、学习 、创业、财富、爱情与人生
scikit-learn: machine learning in Python
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Deep Learning for humans
Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Clone a voice in 5 seconds to generate arbitrary speech in real-time
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
Hindsight: Agent Memory That Learns
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
Deepfakes Software For All
A markup-based typesetting system that is powerful and easy to learn.