Machine Learning (ML)

Teaching computers to learn from data without explicit programming.

About this Exam

ML is a subset of AI covering supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), and reinforcement learning. Core to modern AI systems.

Subjects & Topics Covered

• Linear & Logistic Regression
• Decision Trees, Random Forests
• Support Vector Machines
• K-Means & Hierarchical Clustering
• Neural Networks
• XGBoost, LightGBM
• Feature Engineering
• Model Evaluation Metrics

Preparation Tips

• Math foundation: Linear Algebra + Probability
• Python with NumPy, Pandas, Scikit-learn
• Andrew Ng ML Specialization (Coursera)
• Hands-on Machine Learning by Aurélien Géron
• Build projects: predict house prices, classify images, sentiment analysis
• Kaggle datasets for practice