anthropics / prompt-eng-interactive-tutorial
Anthropic's Interactive Prompt Engineering Tutorial
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Anthropic's Interactive Prompt Engineering Tutorial
Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
📚 从零开始的大语言模型原理与实践教程
Neural Networks: Zero to Hero
《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
Examples and guides for using the OpenAI API
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.
Unified Training of Universal Time Series Forecasting Transformers
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Course Files for Complete Python 3 Bootcamp Course on Udemy
Anthropic's educational courses
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
PyTorch code and models for the DINOv2 self-supervised learning method.
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API