AI Study Python Implementations

This project implements the course examples from:

D:\cache\workspace\test\study\chapters

The code is organized by chapter under ai_study/chapters. Each module exposes:

• TITLE
• chapter-specific helper functions
• run(), which returns a small runnable demo result
• a standalone script entry, so each chapter can be run by itself

Usage

List all standalone chapter commands:

python main.py

Run a chapter directly:

python -m ai_study.chapters.machine_learning_workflow

Other examples:

python -m ai_study.chapters.ai_overview
python -m ai_study.chapters.supervised_learning
python -m ai_study.chapters.advanced_moe

The examples intentionally use the Python standard library only. This keeps the project runnable even before installing packages such as NumPy, pandas, scikit-learn, or PyTorch. The Spring AI and LangChain4j chapters are represented as Python-side engineering pattern mappings because their original course material is Java-focused.