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Iot Machine Learning Applications In Telecom Energy And Agriculture Puneet Mathur

  • SKU: BELL-11359670
Iot Machine Learning Applications In Telecom Energy And Agriculture Puneet Mathur
$ 31.00 $ 45.00 (-31%)

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Iot Machine Learning Applications In Telecom Energy And Agriculture Puneet Mathur instant download after payment.

Publisher: Apress
File Extension: PDF
File size: 7.27 MB
Pages: 278
Author: Puneet Mathur
ISBN: 9781484255483, 1484255488
Language: English
Year: 2020

Product desciption

Iot Machine Learning Applications In Telecom Energy And Agriculture Puneet Mathur by Puneet Mathur 9781484255483, 1484255488 instant download after payment.

Apply machine learning using the Internet of Things (IoT) in the agriculture, telecom, and energy domains with case studies. This book begins by covering how to set up the software and hardware components including the various sensors to implement the case studies in Python. The case study section starts with an examination of call drop with IoT in the telecoms industry, followed by a case study on energy audit and predictive maintenance for an industrial machine, and finally covers techniques to predict cash crop failure in agribusiness. The last section covers pitfalls to avoid while implementing machine learning and IoT in these domains. After reading this book, you will know how IoT and machine learning are used in the example domains and have practical case studies to use and extend. You will be able to create enterprise-scale applications using Raspberry Pi 3 B+ and Arduino Mega 2560 with Python. What You Will Learn Implement machine learning with IoT and solve problems in the telecom, agriculture, and energy sectors with Python Set up and use industrial-grade IoT products, such as Modbus RS485 protocol devices, in practical scenarios Develop solutions for commercial-grade IoT or IIoT projects Implement case studies in machine learning with IoT from scratch Who This Book Is For Raspberry Pi and Arduino enthusiasts and data science and machine learning professionals.

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