🤖 PackIA: Machine Learning and AI
From fine-tuning to agents with the best frameworks
Direct answer: From fine-tuning to agents with the best frameworks This pack brings together 8 resources for Claude, Claude Code, ChatGPT Codex.
Build with LangGraph, CrewAI, and the OpenAI Agents SDK: RAG, LLM evaluation, fine-tuning, and multi-agent orchestration with up-to-date guides and production patterns.
Included in the Completo — $50
Plans are cumulative: the Pro Plan includes all Essential Plan packs, and the Complete Plan includes all packs (Essential + Pro). This pack unlocks with the Completo ($50).
Buy with the Completo ($50) Or build your custom plan
For Claude: the skills, MCP servers, prompts, and guides in this pack are used in conversation with Claude, which consults them while working with your files and connected services. View for Claude: only the resource types compatible with Claude (Skill, MCP Server, Prompt collection, Guide). The full pack has 8 resources.
Use cases
- A complete RAG pipeline with answer-quality evaluation
- A multi-agent team with CrewAI for your business case
- A prompt evaluation system with datasets and scorers
Master prompt: Agentic ML Engineer
You are an ML engineer. Problem: {problem} with data {data}. 1) Decide the architecture: pure LLM, RAG, or fine-tuning, with cost/quality criteria, 2) implement the prototype with {framework} including context management and tools, 3) define evaluation: a golden-answer dataset, metrics (faithfulness, relevance), and judges, 4) a production plan: caching, observability, and security guardrails.
Included resources (3)
- claude-api (Skill, anthropics/skills, ★ 176.6k · official) — Claude API reference: models, pricing, parameters, streaming, tool use, MCP, and token counting. GitHub
- mcp-builder (Skill, anthropics/skills, ★ 176.6k · official) — Official guide for creating high-quality MCP servers in Python (FastMCP) or TypeScript, with tools and evaluation suites. GitHub
- Prompt Engineering Guide (Prompt collection, dair-ai/Prompt-Engineering-Guide, ★ 78.4k) — Guide, papers, and notebooks on prompt engineering, RAG, and agents: few-shot, CoT, and self-consistency. GitHub