Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Exploring AI and ML Strategies for Crop Health Monitoring and Management Description An account of the resource This chapter offers a thorough examination of machine learning (ML) and artificial intelligence (AI) approaches designed especially for agricultural crop health monitoring. The story starts with a basic introduction to AI and ML ideas and then covers supervised and unsupervised learning approaches, the fundamentals of reinforcement learning, and the significance of high-quality data preparation in agricultural settings. This chapter explores the use of deep learning architectures and neural networks, explaining how they can be used to simulate human brain activity and how they can be used in picture identification to identify crop diseases. A detailed analysis is conducted of the practical aspects of ML for agriculture, encompassing feature engineering and model assessment methodologies. Additionally, the chapter highlights the ethical issues involved in the proper application of AI/ML models in agricultural contexts. These kinds of applications. In conclusion, the chapter discusses obstacles, offers predictions for future developments, and discusses new lines of inquiry for AI and ML research related to crop health monitoring. Through this thorough research, the chapter seeks to offer insightful information on the transformative potential of AI/ML approaches in supporting efficient and sustainable agriculture practices for improved crop health management. (Publisher name) (publishing year) all right reserved. Creator An entity primarily responsible for making the resource Nanjundan P.; Indu P.V.; Thomas L. Source A related resource from which the described resource is derived Sustainable Farming through Machine Learning Enhancing: Productivity and Efficiency, pp. 1-15. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003484608-1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003484608-1</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212009880&amp;doi=10.1201%2F9781003484608-1&amp;partnerID=40&amp;md5=b37fce903fbdd9fb5fbe53860b9fef42" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212009880&amp;doi=10.1201%2f9781003484608-1&amp;partnerID=40&amp;md5=b37fce903fbdd9fb5fbe53860b9fef42</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-104025478-3; 978-103277749-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Nanjundan P., Department of Data Science, CHRIST University, Pune Lavasa Campus, Maharashtra, Lavasa, India; Indu P.V., Department of Data Science, CHRIST University, Pune Lavasa Campus, Maharashtra, Lavasa, India; Thomas L., Department of Psychology, CHRIST University, Pune Lavasa Campus, Maharashtra, Lavasa, India