Name: Machine Learning and AI Technology for Agricultural Applications (en Inglés)
SKU: 68195507
Price: 193.99 USD
Availability: InStock
Author: Swain, Kishore Chandra; Singha, Chiranjit; Sahoo, Satiprasad

portada Machine Learning and AI Technology for Agricultural Applications (en Inglés)

Machine Learning and AI Technology for Agricultural Applications (en Inglés)

Formato

Libro Físico

Editorial

Academic Press

Autor

Swain, Kishore Chandra; Singha, Chiranjit; Sahoo, Satiprasad

Año

2026

Idioma

Inglés

N° páginas

300

Encuadernación

Tapa Blanda

ISBN13

9780443450501

Machine Learning and AI Technology for Agricultural Applications (en Inglés)

Swain, Kishore Chandra; Singha, Chiranjit; Sahoo, Satiprasad (Autor) · Academic Press · Tapa Blanda

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Reseña del libro "Machine Learning and AI Technology for Agricultural Applications (en Inglés)"

Machine Learning and AI Technology in Agricultural Applications offers a comprehensive overview of how artificial intelligence and machine learning are transforming the agricultural industry. By delving into image processing and advanced data analysis, the book demonstrates how technology addresses modern agricultural challenges, including climate change, urbanization, and increasing global populations. It emphasizes the importance of integrating sensors and data collection methods to generate vast pools of information, which can be efficiently analyzed through AI-driven solutions. The text lays a strong foundation for understanding the role of technological innovation in supporting sustainable and secure food production. Beyond introducing core machine learning models such as random forest, support vector machines, logistic regression, and decision trees, the book highlights the centralization of critical agricultural data in the cloud. This resource benefits both students and seasoned agricultural scientists, providing practical insights for optimizing crop yields, monitoring soil and weather conditions, and managing resources like fertilizers and pesticides. The book also explores the rapid analysis of complex datasets, empowering users to make informed, timely decisions in real-world agricultural scenarios.