Mahesh Kumar Prajapat

This book is a platform for anyone who wishes to explore Artificial Intelligence in the field of agriculture from scratch or broaden their understanding and its uses. This book offers a practical, hands-on exploration of Artificial Intelligence, machine learning, deep Learning, computer vision and Expert system with proper examples to understand. This book also covers the basics of python with example so that any anyone can easily understand and utilize artificial intelligence in agriculture field. This book is divided into two parts wherein first part talks about the artificial intelligence and its impact in the agriculture with all its branches and their basics. The second part of the book is purely implementation of algorithms and use of different libraries of machine learning, deep learning and computer vision to build useful and sightful projects in real time which can be very useful for you to have better understanding of artificial intelligence. After reading this book, the reader will an understanding of what Artificial Intelligence is, where it is applicable, and what are its different branches, which can be useful in different scenarios. The reader will be familiar with the standard workflow for approaching and solving machine-learning problems, and how to address commonly encountered issues. The reader will be able to use Artificial Intelligence to tackle real-world problems ranging from crop health prediction to field surveillance analytics, classification to recognition of species of plants etc. Note: T&F does not sell or distribute the hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka. This title is co-published with NIPA.

This book is a comprehensive resource for individuals who wish to explore the potential of Artificial Intelligence (AI) in agriculture, either for the purpose of gaining a foundational understanding or expanding their existing knowledge. The book provides readers with a practical, hands-on approach to learning about AI, machine learning, deep learning, computer vision, and expert systems, with real-world examples to aid comprehension. Furthermore, the book includes an introduction to the basics of Python programming, making it accessible to readers with little or no prior programming experience. The book is divided into two parts: the first part covers the fundamentals of AI in agriculture, including its various branches and their applications. The second part focuses on the implementation of algorithms and the use of different machine learning, deep learning, and computer vision libraries to develop practical and insightful projects. Upon completion of this book, readers will have gained an understanding of the various branches of AI and their applicable scenarios, as well as the standard workflow for approaching and solving machine-learning problems. Additionally, readers will be equipped with the skills necessary to tackle real-world problems in the agriculture sector, such as crop health prediction, field surveillance analytics, and the recognition of plant species. With this knowledge, readers will be well-prepared to leverage the power of AI in the agriculture field.