Complete software development lifecycle from requirements to deployment. Use when (1) starting a new project from scratch, (2) need structured end-to-end development process, (3) require comprehensive documentation and quality gates at each phase.
专业的AI Agent(AI Agents)顾问助手,探索 AI Agent 框架和应用。当用户询问以下问题时使用:(1) 技术选型和对比 (2) 使用指南和最佳实践 (3) 问题诊断和解决 (4) 资源推荐 (5) 常见问题解答
Comprehensive CV learning assistant. Use when studying image processing, object detection, segmentation, or any CV tasks. Helps with algorithm understanding, implementation, and model optimization.
Comprehensive DL learning assistant. Use when studying neural networks, CNN, RNN, LSTM, Transformer, or any DL architectures. Helps with network design, training strategies, debugging, and optimization techniques.
Comprehensive LLM learning assistant. Use when studying transformer architecture, attention mechanisms, pre-training, fine-tuning, or prompt engineering. Helps with understanding LLM principles and practical applications.
Comprehensive ML learning assistant. Use when studying supervised learning, unsupervised learning, regression, classification, clustering, or any ML concepts. Helps with algorithm understanding, implementation guidance, model evaluation, and practical applications.
Comprehensive MV learning assistant for industrial computer vision applications. Use when studying image processing, feature extraction, object detection, quality inspection, or automation systems. Helps with (1) concept explanation with real-world examples, (2) OpenCV code analysis and debugging, (3) homework guidance without direct answers, (4) lab experiment setup and troubleshooting, (5) quiz generation for self-assessment, (6) knowledge summarization and review materials, (7) vision system design and optimization, (8) research paper reading and comprehension, (9) generating MV lab code with bilingual comments.
NLP course learning assistant. Use when (1) doing NLP labs/assignments, (2) understanding NLP concepts (tokenization, embeddings, transformers), (3) implementing NLP algorithms, (4) debugging NLP code, (5) preparing for NLP exams.