Can I use this for cloud-native AI development?

Absolutely. It contains specific deployment patterns for AWS services including SageMaker for model hosting and Bedrock for foundational model access.

Does this skill help with LLM application testing?

Yes, it includes specialized guidance for LLM judge evaluation patterns and integration with tools like LangSmith to ensure output quality.

What machine learning frameworks are supported?

The skill provides patterns and best practices for popular frameworks including Scikit-learn, TensorFlow, and XGBoost.

How does it handle RAG and vector databases?

It provides architectures for RAG systems, embedding management, and advanced knowledge graph integration using Graphiti.

ML & AI Engineering Assistant

Name: ML & AI Engineering Assistant
Author: diegouis

bydiegouis

•

データサイエンスとML

Accelerates the development of machine learning models and AI systems through expert guidance on MLOps, RAG architectures, and model deployment.

The ML & AI Engineering Assistant is a comprehensive skill designed to guide developers through the entire machine learning lifecycle. From initial model training and feature engineering to complex MLOps pipelines and LLM-powered application development, this skill provides standardized patterns for success. It includes deep support for RAG systems, knowledge graph integration via Graphiti, and experiment tracking with MLflow. Whether you are optimizing inference on AWS SageMaker or building sophisticated evaluation frameworks using the 'LLM judge' pattern, this skill ensures your AI infrastructure is scalable, measurable, and production-ready.

主な機能

01Model deployment patterns for AWS SageMaker and Bedrock

02Experiment tracking integration for MLflow and Weights & Biases

03Standardized LLM evaluation and prompt engineering frameworks

042 GitHub stars

05Advanced RAG system design with vector stores and knowledge graphs

06End-to-end MLOps pipeline orchestration and validation gates

ユースケース

01Deploying scalable inference APIs and monitoring for data drift in production

02Automating model training workflows and experiment tracking for deep learning projects

03Building and evaluating a production-grade RAG pipeline with Knowledge Graph integration

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add diegouis/provectus-marketplace ml-ai-assistant

For use in Claude.ai and ChatGPT

Download Skill