OpenAI safety bug bounty launches with MCP prompt injection and data exfiltration in scope. Here is why the move matters for AI agent security.

Learn how to build multimodal AI applications with Python. This guide covers OpenAI GPT-4 Vision API, image captioning with transformers, audio transcription with Whisper, combining modalities, and...

Learn how to make machine learning models interpretable with Python using SHAP and LIME. This guide covers feature importance, local explanations, visualizations, and practical examples with gradie...

Complete guide to sentiment analysis with Python using TextBlob, VADER, scikit-learn, and Hugging Face Transformers. Includes building a REST API for production deployment.

Learn how to fine-tune large language models using Python with LoRA, QLoRA, Hugging Face Transformers, and PEFT. Covers dataset preparation, training, evaluation, and deployment.

Learn how to use AutoML in Python with Auto-sklearn, TPOT, and H2O AutoML. This guide covers automated model selection, hyperparameter tuning, and pipeline optimization with practical examples.

Learn how to build a Retrieval-Augmented Generation (RAG) system with Python using ChromaDB, FAISS, OpenAI embeddings, and LangChain. Complete working examples included.

学习如何使用 OpenAI API 和 LangChain 在 Python 中构建自主的 AI agents。本指南涵盖 agent loop、tool 的使用、memory 以及一个实用的 research agent 示例。

通过一个实用的首个服务器教程、MCP 的核心概念，以及从自定义脚本到可复用 AI 工具的最快路径，用 Python 学习 Model Context Protocol。

学习如何在 Python 中使用 OpenAI Agents SDK，构建带有 tool 调用、tracing 和 handoff 的多智能体工作流，并采用整洁、可用于生产的结构。