커뮤니티 중심의 저장소는 누구나 인공지능을 배우는 데 도움을 줍니다.runnable example,concise descriptions,visual guides for baseal to modern AI topic.

⭐ 왜 이 Repo Exists

• 💻 Practical Examples - 모든 코드는 아웃 박스 실행
• Visual Learning - Mermaid 다이어그램과 명확한 설명
• AI **빠른 시작 ** - "AI에서 5 분"모든 항목에 대한 요약
• Comprehensive - ML 기초부터 최첨단 기술
• 12.1 Curated Resources - 최고의 튜토리얼, 문서 및 학습 경로

⭐ **이 repo ** 업데이트를 따르고 기여!

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⭐ 빠른 시작

##1. 복제 및 설치

##2. 환경 구성

##3. 실행 예제

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저장소 구조

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학습 경로

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AI 및 기계 학습에 새로운 경우 완벽한:

1. 01 Foundations - 여기 시작! ML 기초 알아보기

• 선형 회귀 - Predict 연속 값
• Perceptron - 첫 번째 신경 네트워크
• 리소스 - Curated 초보자 가이드

2. 02 LLMs - 현대 AI의 이해

• LLMs 및 어떻게 작동합니까?
• 첫 번째 LLM 예제 실행
• 상호 작용하는 Jupyter 탐험

3. 명세.

🧠 AI-Essentials — The Ultimate AI Learning Directory

A community-driven repository helping anyone learn Artificial Intelligence — with runnable examples, concise explanations, and visual guides for foundational to modern AI topics.

⭐ Why This Repo Exists

• 💻 Practical Examples - All code runs out-of-the-box
• 📊 Visual Learning - Mermaid diagrams and clear explanations
• ⚡ Quick Start - “AI in 5 Minutes” summaries for every topic
• 🎯 Comprehensive - From ML fundamentals to cutting-edge techniques
• 🔗 Curated Resources - Best tutorials, docs, and learning paths

⭐ Star this repo to follow updates and contribute!

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🚀 Quick Start

1. Clone and Install

# Clone the repository
git clone https://github.com/6NineLives/AI-Essentials.git
cd AI-Essentials

# Python setup
python -m venv .venv
source .venv/bin/activate  # Windows: .\.venv\Scripts\activate
pip install -r requirements.txt

# Node.js setup
npm install

2. Configure Environment

# Copy example environment file
cp .env.example .env

# Edit .env and add your API keys
# OPENAI_API_KEY=your_key_here
# PINECONE_API_KEY=your_key_here (optional)

3. Run Examples

# Foundations
python 01_Foundations/linear_regression.py
python 01_Foundations/perceptron_example.py

# LLMs
python 02_LLMs/openai_example.py
python 02_LLMs/transformers_example.py
jupyter notebook 02_LLMs/llm_basics.ipynb

# RAG
python 03_RAG/rag_pipeline.py
python 03_RAG/vectorstore_setup.py

# MCP
python 04_MCP/mcp_server_example.py
node 04_MCP/client_example.js

# Agents
python 05_Agents/openai_agent.py
python 05_Agents/crewai_agent_example.py

# Vector Databases
python 06_Vector_Databases/chromadb_example.py
python 06_Vector_Databases/pinecone_example.py

# Prompt Engineering
python 07_Prompt_Engineering/examples/system_prompt_tuning.py

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📂 Repository Structure

AI-Essentials/
├── 01_Foundations/          # ML fundamentals
│   ├── README.md            # Linear regression & perceptron concepts
│   ├── linear_regression.py # Working example with visualization
│   ├── perceptron_example.py # Neural network basics
│   └── resources.md         # Curated learning materials
│
├── 02_LLMs/                 # Large Language Models
│   ├── README.md            # LLM concepts and architecture
│   ├── openai_example.py    # OpenAI API usage
│   ├── transformers_example.py # Hugging Face transformers
│   ├── llm_basics.ipynb     # Interactive Jupyter notebook
│   └── ai_in_5_minutes.md   # Quick LLM overview
│
├── 03_RAG/                  # Retrieval-Augmented Generation
│   ├── README.md            # RAG pipeline explanation