Applications of Machine Learning in Power Electronics for Integration of Renewable Energy Sources explores how AI techniques enhance renewable energy systems through optimized power electronics. This essential guide introduces machine learning applications for improving control, predictive maintenance, and fault detection across renewable sources like solar and wind. With real-world case studies and practical insights, the book equips engineers, researchers, and students with tools to tackle challenges in renewable integration, power quality, and system reliability. An invaluable resource for both beginners and experts, this book sheds light on AI-driven innovations shaping a sustainable energy future.