Python for Agriculturists
Muhammad Azhar Iqbal
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Add to basketSold by buchversandmimpf2000, Emtmannsberg, BAYE, Germany
AbeBooks Seller since January 23, 2017
Condition: New
Quantity: 1 available
Add to basketThis item is printed on demand - Print on Demand Titel. Neuware -This book aims to introduce agriculturists, particularly those with non-computing backgrounds, to the Python programming language. Python's simplicity, versatility, and extensive library support make it an ideal tool for addressing data science and machine learning challenges. This book focuses on the application of Python in various agricultural fields such as Agronomy, Entomology, Plant Pathology, Forestry, Horticulture, Food Technology, Farm Machinery, and Animal Sciences. It underscores the significance of programming skills in empowering agriculturists to analyze data, optimize resources, and automate routine tasks, thereby enhancing productivity and contributing to sustainable agricultural practices. By bridging the gap between traditional agricultural knowledge and modern computing techniques, this book serves as a valuable resource for agriculturists aiming to advance their careers and improve agricultural outcomes.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch.
Seller Inventory # 9783032014412
This book aims to introduce agriculturists, particularly those with non-computing backgrounds, to the Python programming language. Python's simplicity, versatility, and extensive library support make it an ideal tool for addressing data science and machine learning challenges. This book focuses on the application of Python in various agricultural fields such as Agronomy, Entomology, Plant Pathology, Forestry, Horticulture, Food Technology, Farm Machinery, and Animal Sciences. It underscores the significance of programming skills in empowering agriculturists to analyze data, optimize resources, and automate routine tasks, thereby enhancing productivity and contributing to sustainable agricultural practices. By bridging the gap between traditional agricultural knowledge and modern computing techniques, this book serves as a valuable resource for agriculturists aiming to advance their careers and improve agricultural outcomes.
Muhammad Azhar Iqbal completed his PhD in Communication and Information Systems in 2012 from Huazhong University of Science and Technology (HUST), China. Later, he worked in different universities in different positions. Prior to his current tenure as Assistant Professor at the University of Leeds, Dr. Azhar held significant roles (as Teaching Fellow) at Lancaster University (LU, United Kingdom), (as Associate Professor) at Southwest Jiaotong University (SWJTU, China), and (as Associate Professor) at Capital University of Science and Technology (CUST, Pakistan). With over 13 years of teaching experience in Computer Science, he has taught a variety of core and advanced computer science courses at both undergraduate and postgraduate levels in universities across Pakistan, China, and the UK.
He holds senior membership in IEEE and a fellowship from the Higher Education Academy, reflecting his commitment to academic excellence and professional development. His research interests include computer networks, Internet of Things (IoT), and digital agriculture, and he has published numerous collaborative research works in these areas.
He is the author of three textbooks on the topics of Computer Network Simulations, Internet of Things (IoT), and Digital Agriculture. These textbooks aim to bridge the gap between theoretical concepts and practical applications, providing students with a soild understanding of networking, IoT, and digital agriculture systems. The inspiration for writing the first two textbooks came from his observation that while theoretical concepts of computer networks and IoT are easy to comprehend at an abstract level, students often struggle to understand the practical importance and placement of networking/IoT components in a system. The third textbook on Digital Agriculture addresses the development and deployment of IoT-based digital agriculture systems, including precision and smart farming, and aims to provide a firm foundation for understanding the enabling technologies that support crop and livestock production, improvement, and protection.
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