data-ai-skills
Master machine learning, data engineering, AI engineering, LLMs, prompt engineering, and MLOps. Build intelligent systems with Python.
Skills correspondant au nom, à la description ou à l’auteur GitHub.
Master machine learning, data engineering, AI engineering, LLMs, prompt engineering, and MLOps. Build intelligent systems with Python.
Comprehensive data science, machine learning, and AI guide covering Python, deep learning, NLP, LLMs, prompt engineering, and MLOps. Use when building AI models, data pipelines, or machine learning systems.
Complete backend development guide covering Node.js, Python, Go, Java, PHP, databases, APIs, authentication, and server architecture. Use when building server applications, APIs, or backend systems.
Production-grade backend patterns for Node.js, Python, Go, and Java/Spring frameworks
Spawn a new terminal window to run CLI commands (ffmpeg, curl, python, etc.). Use for non-AI command execution.
Split large Python files into multiple files organized as a package. Use when user says "split this file", "this file is too big", "break this into multiple files", or similar requests for Python (.py) files.
Provide a reusable pattern for memoizing deterministic function calls to reduce latency and repeated computation. Backed by the `python` diskcache package. Use skill when updating or editing everything.
Clean Architecture and Cosmic Python guidance for well-tested, layered Python systems. Use for designing Python projects with layered architecture (models, adapters, services, entrypoints), enforcing Clean Code...
Programmatically interact with Domino using python-domino SDK and REST APIs. Covers authentication, running jobs, managing projects, file operations, model deployment, and automation. Use when automating Domino...
Use the domino-data Python SDK (dominodatalab-data) for programmatic data access in Domino. Covers DataSourceClient for SQL queries and object storage, DatasetClient for dataset files, TrainingSets for ML data...
Use buzzllm CLI to perform web searches, execute Python code in Docker, search/analyze local codebases, or generate code change blocks. Trigger when user asks for web search, Python execution, code analysis, or...
Autonomous task execution with library discovery, 3-tier validation, and atomic git commits. Integrates with Shannon CLI Python modules for platform-specific execution. Invokes /shannon:wave for code generation...
Use when testing Claude Code plugins programmatically, building SDK applications, encountering plugin loading failures (plugins array empty), getting AttributeError on message.type, or needing verified Claude A...
Deploy Flask server to remote machine (185.96.221.52). Stops remote server, copies files via scp, restarts server, and verifies. Use when deploying Python server updates to remote Mac mini.
Stop local Flask server running on port 8080. Kills process cleanly using lsof or PID file. Use when stopping local Python development server.
Start Flask server locally for development. Runs server in foreground or background with nohup. Use when starting local Python server for testing or development.
Format and analyze Python code using ruff (formatting/linting) and ty (static type checking). Use when the user asks to format Python code, run linting, check types, fix code style issues, or analyze Python cod...
Implement native Rust ML inference with Candle framework. Use when building GPU-accelerated ML pipelines without Python dependencies.
Bridge Rust and Python using PyO3 with proper GIL handling and async compatibility. Use when integrating Python ML models or libraries.
WHEN: General Python code review, PEP8 compliance, type hints, Pythonic patterns WHAT: PEP8/style check + Type hint validation + Pythonic idioms + Error handling + Documentation WHEN NOT: FastAPI → fastapi-revi...
WHEN: Pandas/NumPy code review, data processing, vectorization, memory optimization WHAT: Vectorization patterns + Memory efficiency + Data validation + Performance optimization + Best practices WHEN NOT: Web f...
WHEN: Flask project review, Blueprint structure, extensions, request handling WHAT: Blueprint organization + Extension patterns + Request/response handling + Configuration + Testing WHEN NOT: FastAPI → fastapi-...
WHEN: Machine Learning/Deep Learning code review, PyTorch/TensorFlow patterns, Model training optimization, MLOps checks WHAT: Model architecture review + Training patterns + Data pipeline checks + GPU optimiza...
WHEN: FastAPI project review, Pydantic models, async endpoints, dependency injection WHAT: Pydantic validation + Dependency injection + Async patterns + OpenAPI docs + Security WHEN NOT: Django → django-reviewe...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.