class AIEngineer:
    def __init__(self):
        self.skills = {
            # 深度学习
            "deep_learning": {
                "frameworks": ["PyTorch", "TensorFlow", "Keras"],
                "model_architectures": ["CNN", "RNN", “LSTM”, "Transformer", "BERT"],
                "training_optimization": ["混合精度训练", "梯度累积", "学习率调度策略"],
                "distributed_training": ["DeepSpeed", "Hadoop", "Spark"],
                "model_compression": ["量化(INT8/FP16)", "剪枝", "知识蒸馏"]
            },
            
            "learning_strategy": {
                "learning_paradigms": [
                    "零样本学习(Zero-shot)", 
                    "少样本学习(Few-shot)",
                    "半监督学习", 
                    "弱监督学习",
                ],
                "advanced_techniques": [
                    "检索增强生成(RAG)",
                    "提示工程", 
                    "模型微调策略",
                    "多模态学习"
                ]
            },
            
            # 全栈开发
            "fullstack_development": {
                "frontend": ["Vue", "Node.js", "TypeScript"],
                "backend": ["FastAPI", "SpringBoot"],
                "databases": ["MySQL", "Redis", "SQLite", "SQL Server"],
                "devops": ["Docker", "Linux", "Nginx"]
            },
            
            # 编程语言
            "programming_languages": {
                "primary": ["Python", "C", "C++", "Java"],
                "secondary": ["SQL", "Shell", "HTML", "CSS"]
            }
        }
    
    def get_tech_stack(self):
        """返回完整技术栈"""
        stack = []
        for category, skills in self.skills.items():
            for subcategory, items in skills.items():
                stack.extend(items)
        return stack
    
    def describe_experience(self):
        return {
            "ai_engineering": "具备从模型设计、训练优化到生产部署的完整工程能力",
            "large_scale_training": "拥有大规模模型分布式训练实战经验",
            "model_compression": "精通模型压缩技术，实现资源受限场景高效部署",
            "fullstack_delivery": "具备完整的Web应用及小程序开发交付能力"
        }

# 实例化
engineer = AIEngineer()
print("🎯 技术专长:", engineer.describe_experience())
print("🚀 技术栈:", engineer.get_tech_stack())