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Название: No-Code: AI Concepts and Applications in Machine Learning, Visualization, and Cloud Platforms
Автор: Min Soo Kang, Sung Yul Park, Myung-Ae Chung, Dong-hun Han
Издательство: World Scientific Publishing
Год: 2024
Страниц: 403
Язык: английский
Формат: pdf (true)
Размер: 134.8 MB
This book is a beginner-friendly guide to Artificial Intelligence (AI), ideal for those with no technical background. It introduces AI, Machine Learning, and Deep Learning basics, focusing on no-code methods for easy understanding. The book also covers data science, data mining, and big data processing, maintaining a no-code approach throughout. Practical applications are explored using no-code platforms like Microsoft Azure Machine Learning and AWS SageMaker. Readers are guided through step-by-step instructions and real-data examples to apply learning algorithms without coding. Additionally, it includes the integration of business intelligence tools like Power BI and AWS QuickSight into machine learning projects.This guide bridges the gap between AI theory and practice, making it a valuable resource for beginners in the field.
Автор: Min Soo Kang, Sung Yul Park, Myung-Ae Chung, Dong-hun Han
Издательство: World Scientific Publishing
Год: 2024
Страниц: 403
Язык: английский
Формат: pdf (true)
Размер: 134.8 MB
This book is a beginner-friendly guide to Artificial Intelligence (AI), ideal for those with no technical background. It introduces AI, Machine Learning, and Deep Learning basics, focusing on no-code methods for easy understanding. The book also covers data science, data mining, and big data processing, maintaining a no-code approach throughout. Practical applications are explored using no-code platforms like Microsoft Azure Machine Learning and AWS SageMaker. Readers are guided through step-by-step instructions and real-data examples to apply learning algorithms without coding. Additionally, it includes the integration of business intelligence tools like Power BI and AWS QuickSight into machine learning projects.This guide bridges the gap between AI theory and practice, making it a valuable resource for beginners in the field.