AI Scratchpad

Welcome to AI Scratchpad

This is my open notebook for exploring the world of AI and Machine Learning. I learn by building, breaking, and experimenting, documenting everything along the way. Here, you’ll find practical guides and working code. I hope you enjoy reading it as much as I enjoy writing it.

Feature Scaling Part 3: Advanced Techniques

Fundamentals

Data Preprocessing

Scaling

Sparse Data

Series: Feature Scaling

Beyond the basics: explore MaxAbs Scaling, Power and Quantile Transformations, Vector Normalization, and custom scaling strategies. Includes Python and R code examples with a focus on sparse data and practical ML use cases.

Aug 27, 2025

January Tabaka

Feature Scaling Part 2: Standardization, Normalization & Robust Scaling

Fundamentals

Data Preprocessing

Scaling

Standardization

Normalization

Robust Scaling

Series: Feature Scaling

A practical guide to the three most common feature scaling techniques in machine learning: standardization, normalization, and robust scaling. Includes code examples in Python and R, and an analysis of their sensitivity to outliers.

Aug 13, 2025

January Tabaka

Feature Scaling Part 1: When (and Why) to Scale Data in Machine Learning

Fundamentals

Data Preprocessing

Scaling

Series: Feature Scaling

Learn why feature scaling is a critical preprocessing step in machine learning. This guide explains which models are sensitive to data scale and provides a clear visual demonstration.

Jul 30, 2025

January Tabaka

Categories

Feature Scaling Part 3: Advanced Techniques

Feature Scaling Part 2: Standardization, Normalization & Robust Scaling

Feature Scaling Part 1: When (and Why) to Scale Data in Machine Learning