ml-toolkit

🧠 Machine Learning Toolkit

A curated, hands-on collection of Machine Learning methods with clear explanations, minimal code wrappers, and dual-level insights:

• 🔬 For technical users: see internal mechanics, diagnostics, and decision logic
• 📊 For business users: skim final insights, performance highlights, and takeaway summaries

🎯 Built to help you understand, reuse, and communicate ML workflows with confidence.

🧩 What's Inside

Category	Notebooks
Supervised Learning	Classification, Regression Time Series Forecasting
Unsupervised Learning	Clustering, Dimensionality Reduction, Association Rule Learning
Semi-Supervised Learning	Label Propagation, Pseudo Labeling

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🛠️ Design Principles

• Minimal magic: Code-first approach with visible logic
• Tutorial-style: Key theory as collapsible notes, not distractions
• Config-ready: Structure encourages reusability across datasets and tasks
• Business-minded: Final cell outputs explain what it means — not just what it does

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