Sleep Disorder Data Preprocessing in Machine Learning

Deploying Machine Learning (ML) on the cloud doesn’t begin with algorithms—it begins with data preprocessing.

In this Masterclass, learn how to clean, transform, and prepare a real-world sleep disorder dataset for ML models. From handling missing values to encoding categorical variables and scaling features, discover the essential preprocessing steps that make your cloud ML pipelines accurate and reliable.

💡 What you’ll learn in this session:

Understanding datasets and structure

Handling missing & noisy data

Encoding categorical variables (Label & One-Hot Encoding)

Feature scaling & normalization

🚀 Take the next step in your career with Imarticus Learning:

Postgraduate Program in Data Science and Analytics (PGA) → 6 months | 25+ projects | 100% job assurance