INTRODUCTION TO MACHINE LEARNING WITH PYTHON: A GUIDE FOR DATA SCIENTIST
Introduction to Machine Learning with Python: A Guide for Data Scientists is a practical textbook that introduces the core concepts, algorithms, and applications of machine learning using the Python programming language. The book covers data preprocessing, exploratory data analysis, supervised and unsupervised learning, model evaluation, feature engineering, ensemble methods, deep learning fundamentals, and model deployment. It provides hands-on examples using popular Python libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, and PyTorch, enabling readers to build and evaluate machine learning models effectively. Designed for students, researchers, and aspiring data scientists, this book bridges theory and practice, making it an ideal resource for solving real-world data science and artificial intelligence problems.