About the Book: Machine Learning Using Python is a comprehensive beginner-to-intermediate guide that builds a strong foundation in machine learning, data science, and Python programming through a blend of theory and hands-on practice. Covering statistics, probability, exploratory data analysis, supervised learning (linear regression, logistic regression, decision trees, KNN, SVM, random forests, boosting, stacking), recommender systems, text analytics, and unsupervised learning techniques like clustering and dimensionality reduction, the book equips readers with practical, job-ready skills. With real-world case studies and step-by-step implementations using Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn, along with insights into ML explainability and MLOps deployment, it is an essential resource for aspiring data scientists and AI professionals.