ai-ml-technologies

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Master AI, machine learning, LLMs, prompt engineering, and blockchain development. Use when building AI applications, working with LLMs, or developing smart contracts.

⭐1stars🔀0forks📁View on GitHub🕐Updated Dec 31, 2025
[Code Generation]

When & Why to Use This Skill

This Claude skill is a comprehensive technical resource designed to help developers master and implement cutting-edge technologies including Artificial Intelligence, Machine Learning, and Blockchain. It provides expert-level guidance on building AI applications, optimizing Large Language Models (LLMs) through prompt engineering, and developing secure smart contracts, ensuring high-quality code and architectural best practices.

Use Cases

  • AI Application Development: Rapidly prototype and build intelligent applications by integrating OpenAI, Anthropic, or open-source LLMs using frameworks like LangChain.
  • Smart Contract Engineering: Develop, test, and audit decentralized applications (dApps) using Solidity, Hardhat, and Foundry for secure blockchain deployment.
  • Machine Learning Integration: Implement complex data science workflows and model training scripts using PyTorch, TensorFlow, and scikit-learn.
  • Prompt Engineering & Optimization: Design and refine sophisticated prompts and agentic workflows to improve the accuracy and reliability of AI-driven features.
  • Game Engine Scripting: Create advanced game logic and AI behaviors within Unity (C#) or Unreal Engine (C++) environments.
nameai-ml-technologies
descriptionMaster AI, machine learning, LLMs, prompt engineering, and blockchain development. Use when building AI applications, working with LLMs, or developing smart contracts.
sasmp_version"1.3.0"
bonded_agent05-ai-emerging-technologies
bond_typePRIMARY_BOND

AI & Emerging Technologies Skill

Quick Start - OpenAI API

from openai import OpenAI

client = OpenAI(api_key="sk-...")

# Simple completion
response = client.chat.completions.create(
  model="gpt-4",
  messages=[
    {"role": "system", "content": "You are helpful assistant"},
    {"role": "user", "content": "Explain machine learning"}
  ],
  temperature=0.7,
  max_tokens=500
)

print(response.choices[0].message.content)

Core Technologies

AI & LLMs

  • OpenAI API (GPT-4)
  • Claude API (Anthropic)
  • Open-source LLMs (Llama, Mistral)
  • LangChain for applications
  • Vector databases (Pinecone, Weaviate)

Machine Learning

  • TensorFlow / PyTorch
  • scikit-learn
  • XGBoost
  • Hugging Face Transformers

Blockchain & Web3

  • Solidity for smart contracts
  • Web3.js / Ethers.js
  • Hardhat development
  • Foundry

Game Engines

  • Unity (C#)
  • Unreal Engine (C++)
  • Godot (GDScript)

Best Practices

  1. AI Ethics - Consider societal impact
  2. Testing - Rigorous evaluation
  3. Monitoring - Track model performance
  4. Documentation - Clear decision records
  5. Security - Smart contract auditing
  6. Cost Optimization - Minimize API usage
  7. Version Control - Track models and prompts
  8. Responsible AI - Bias and fairness

Resources