IoT Machine Learning Applications in Telecom, Energy, and Agriculture: With Raspberry Pi and Arduino Using Python
Mathur, Puneet
ISBN 10: 1484255488 ISBN 13: 9781484255483
Published by Apress, 2020
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Synopsis:
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.
About the Author:
Puneet Mathur is an author, AI consultant, and speaker who has over 20 years of corporate IT industry experience. He has risen from being a programmer to a third line manager working with multinationals such as HP, IBM, and Dell at various levels. For several years he has been working as an AI consultant through his company Boolbrite International for clients around the globe, by guiding and mentoring client teams stuck with AI and machine learning problems. He also conducts leadership and motivational workshops, and AI-based hands-on corporate workshops. His latest bestselling book, Machine Learning Applications using Python (Apress, 2018), is for machine learning professionals who want to advance their career by gaining experiential knowledge from an AI expert. His other books include The Predictive Program Manager, Prediction Secrets, and Good Money Bad Money.
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Bibliographic Details
Title: IoT Machine Learning Applications in Telecom...
Publisher: Apress
Publication Date: 2020
Binding: Paperback
Condition: New
Edition: 1st ed.
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IoT Machine Learning Applications in Telecom, Energy, and Agriculture (Paperback)
Published by
APress, Berkley, 2020
ISBN 10: 1484255488
ISBN 13: 9781484255483
New
Paperback
First Edition
Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. 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 LearnImplement machine learning with IoT and solve problems in the telecom, agriculture, and energy sectors with PythonSet up and use industrial-grade IoT products, such as Modbus RS485 protocol devices, in practical scenariosDevelop solutions for commercial-grade IoT or IIoT projectsImplement case studies in machine learning with IoT from scratchWho This Book Is ForRaspberry Pi and Arduino enthusiasts and data science and machine learning professionals. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781484255483
Quantity: 1 available
Stock Image
IoT Machine Learning Applications in Telecom, Energy, and Agriculture (Paperback)
Published by
APress, Berkley, 2020
ISBN 10: 1484255488
ISBN 13: 9781484255483
New
Paperback
First Edition
Seller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. 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 LearnImplement machine learning with IoT and solve problems in the telecom, agriculture, and energy sectors with PythonSet up and use industrial-grade IoT products, such as Modbus RS485 protocol devices, in practical scenariosDevelop solutions for commercial-grade IoT or IIoT projectsImplement case studies in machine learning with IoT from scratchWho This Book Is ForRaspberry Pi and Arduino enthusiasts and data science and machine learning professionals. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781484255483
Quantity: 1 available