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About The Author

Rajesh Singh
Rajesh Singh, Lovely Professional University, India and was previously associated with University of Petroleum and Energy Studies, Dehradun as Associate Professor and with additional responsibility as Head, Institute of Robotics Technology (R&D).

Anita Gehlot
Anita Gehlot, Lovely Professional University, India. She has more than ten years of teaching experience with area of expertise embedded systems and wireless sensor networks. She has ten patents in her account

Mahesh Prajapat
Mahesh Prajapat, Lovely Professional University, India

Bhupendra Singh
Bhupendra Singh is Managing Director of Schematics Microelectronics and provides Product design and R & D support to industries and Universities

About The Book

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.

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  1. Start Pages

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  2. Artificial Intelligence

    3 - 7 (5 Pages)
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  3. Learning Python for Artificial Intelligence

    8 - 40 (33 Pages)
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  4. Machine Learning

    41 - 49 (9 Pages)
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  5. Deep Learning

    50 - 63 (14 Pages)
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  6. Computer Vision

    64 - 72 (9 Pages)
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  7. Knowledge Based Expert System

    73 - 82 (10 Pages)
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  8. Tools for Artificial Intelligence

    83 - 96 (14 Pages)
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  9. Important Libraries for AI

    97 - 105 (9 Pages)
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  10. Machine Learning Algorithms

    106 - 136 (31 Pages)
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  11. 10 

    Disease Classification and Detection in Plants

    137 - 150 (14 Pages)
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  12. 11 

    Species Recognition in Flowers

    151 - 167 (17 Pages)
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  13. 12 

    Precision Farming

    168 - 176 (9 Pages)
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