Machine Learning  (English, Hardcover, Dr. Sellappan Palaniappan Dr. Sumit Dhariwal)

Machine Learning changes businesses and lifestyles. A Practitioner's Guide for Machine Learning combines theory and practice for beginners and experts. Machine Learning foundations, relevance, and applications are covered. Chapters end with applying principles to life. Python Fundamentals, the second chapter, teaches model-building programming. Data preprocessing includes cleansing, transformation, and feature engineering. Next, we explore linear regression, decision trees, clustering, and dimensionality reduction in supervised and unsupervised learning. Machine Learning teaches model performance measurement and improvement, whereas Introduction to Neural Networks and Deep Learning covers sophisticated topologies. Language Processing and Reinforcement Learning applications are covered in this book. Through case studies and ethics, real-world applications show impact. Future Directions predicts advanced themes and trends to enhance learning in a changing industry. About 50 Python programs in this book demonstrate Machine Learning in business, finance, agriculture, health, neurology, NLP, and games. These examples explain Machine Learning and show its versatility and strength across fields. Sidebars enhance learning by providing context. This book integrates theory and practice to help you explore Machine Learning, a growing topic.