Machine Learning Fundamentals

This practice exam covers the practical machine learning concepts every ML practitioner and AI engineer needs to know — from data preparation and feature engineering through model training, evaluation, deployment, and monitoring. Questions are framework-agnostic but reference scikit-learn, PyTorch, and Hugging Face where relevant.

• Mastering AI and Machine Learning in the Real World (Morgan Steele, 2025)
• Scikit-learn Documentation — Supervised Learning
• PyTorch Documentation — Neural Networks
• Hugging Face Documentation — Transformers