
Data-Driven Farming
Description
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Data-Driven Farming: Harnessing the Power of AI and Machine Learning in Agriculture is a comprehensive guide that explores how the latest advances in technology can help farmers make better decisions and maximize yields. It offers a detailed overview of the intersection of data, AI, and ML in agriculture and offers real-world examples and case studies that demonstrate how these tools can help farmers improve efficiency, reduce waste, and increase profitability. Exploring how AI and ML can be used to achieve sustainable and profitable farming practices, the book provides an introduction to the basics of data-driven farming, including an overview of the key concepts, tools, and technologies. It also discusses the challenges and opportunities facing farmers in today's data-driven landscape. Covering such topics as crop monitoring, weather forecasting, pest management, and soil health management, the book focuses on analyzing data, predicting outcomes, and optimizing decision-making in a range of agricultural contexts.
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Person
Dr. Syed Nisar Hussain Bukhari holds a PhD in Computer Science from Chandigarh University India. His research interests include artificial intelligence and machine learning, deep learning, applying AI and ML in interdisplinary areas like Agriculture, Health care. His other work areas are bioinformatics, Immunoinformatics and computational biology and has taught courses on Artificial Intelligence and Machine Learning at UG and PG level. He has a proven experience of providing expert advice on the use of technology in different domain.
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