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编程导航 2025 年 AI 开发实战新项目,基于 Spring Boot 3 + Java 21 + Spring AI 构建 AI 恋爱大师应用和 ReAct 模式自主规划智能体YuManus,覆盖 AI 大模型接入、Spring AI 核心特性、Prompt 工程和优化、RAG 检索增强、向量数据库、Tool Calling 工具调用、MCP 模型上下文协议、AI Agent 开发(Manas Java 实现)、Cursor AI 工具等核心知识。用一套教程将程序员必知必会的 AI 技术一网打尽,帮你成为 AI 时代企业的香饽饽,给你的简历和求职大幅增加竞争力。
编程导航 2025 年 AI 开发实战新项目,基于 Spring Boot 3 + Java 21 + Spring AI 构建 AI 恋爱大师应用和 ReAct 模式自主规划智能体YuManus,覆盖 AI 大模型接入、Spring AI 核心特性、Prompt 工程和优化、RAG 检索增强、向量数据库、Tool Calling 工具调用、MCP 模型上下文协议、AI Agent 开发、Cursor AI 工具等核心知识。用一套教程将程序员必知必会的 AI 技术一网打尽,帮你成为 AI 时代企业的香饽饽,给你的简历和求职大幅增加竞争力。
2025 年 AI 编程助手实战项目(作者:程序员鱼皮),基于 Spring Boot 3.5 + Java 21 + LangChain4j + AI 构建智能编程学习与求职辅导机器人,覆盖 AI 大模型接入、LangChain4j 核心特性、流式对话、Prompt 工程、RAG 检索增强、向量数据库、Tool Calling 工具调用、MCP 模型上下文协议、Web 爬虫、安全防护、Vue.js 前端开发、SSE 服务端推送等企业级 AI 应用开发技术。帮助开发者掌握 AI 时代必备技能,熟悉 LangChain 框架,提升编程学习效率和求职竞争力,成为企业需要的 AI 全栈开发人才。
OfflineAI is an artificial intelligence that operates offline and uses machine learning to perform various tasks based on the code provided. It is built using two powerful AI models by Mistral AI.
FxChartAI AI-Agent Trading EA is an open-source MQL5 Expert Advisor for MetaTrader 5 that trades using signals from FxChartAI. It employs trend confirmation, candle tail/trendline analysis, and dynamic order management. Free for personal & commercial use. Contributions welcome.
The Traffic Light Detection and Classification project aims to enhance autonomous driving systems by accurately detecting and classifying traffic lights. The model is designed to generate appropriate physical responses for vehicles equipped with it.
Explore AI Tech Hub, a curated collection of open-source code and resources focused on AI innovations like deep fakes, AI art, and face swapping. A go-to library for developers, researchers, and AI enthusiasts seeking cutting-edge tools and insights.
This repository contains a Python program that performs sentiment analysis on movie reviews, classifying them as either positive or negative. A great project for learning about Natural Language Processing (NLP) and sentiment analysis techniques! 👍👎
[DEMO] simple and fast image-based gender detection with ability to train your own model and use it offline in "low performance" environments e.g. microchips or FPGAs, implemented via C++ / OpenCV