This repository contains the complete set of Jupyter notebooks from Andrew Ng’s Machine Learning Specialization, an introductory course on machine learning. The notebooks cover foundational topics including linear and logistic regression, neural networks built with TensorFlow, decision trees and ensemble methods, unsupervised learning techniques like clustering and anomaly detection, recommender systems, and deep reinforcement learning. Students learn by implementing algorithms using NumPy, scikit-learn, and TensorFlow in hands-on coding exercises.