Machine learning

阿里云百炼平台技术文档知识库（LLM Wiki）。当用户查询百炼模型列表、API 参数、错误码、 应用开发（智能体/RAG/知识库/记忆/插件）、模型对比与定价、SDK/OpenAI 兼容接口、 多模态能力（语音/图片/视频）、Token 计费等百炼相关问题时激活。 包含 models 结构化模型市场数据（含…

Manages and orchestrates prompts in Agent Platform.

Instrument arifOS constitutional AI kernel with Langfuse LLM tracing.

Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits &…

Scaffold, structure, and manage AI/ML projects that run on AzureML.

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics.

Databricks Model Serving endpoint lifecycle and ops.

Generates code that transforms datasets between ML schemas for model training or evaluation.

Behavioral guidelines to reduce common LLM coding mistakes.

Design and evaluate LLM product features, retrieval, validated outputs, latency, and cost controls.

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

Build type-safe LLM applications with DSPy.rb — Ruby's programmatic prompt framework with signatures, modules, agents, and optimization.

Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment…

Train ML models on Databricks.

Databricks Model Serving endpoint lifecycle and ops.

Use when running a Roboflow Workflow over many images or videos with batch processing — Asset Library jobs (the platform stages workspace images for you) or…

Fetch any X/Twitter post as clean LLM-friendly JSON.

Design LLM-as-judge rubrics, direct scores and pairwise comparisons.

Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI…

Search indexed AI and ML jobs, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP

Build production-ready LLM applications, advanced RAG systems, and intelligent agents.

Overview of six AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit…

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

Run assay on a web page you just wrote or changed.