Iot Machine Learning Applications by Mathur Puneet (14 results)

Condition: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Condition: New. In English.

Condition: New. 2020. Paperback. . . . . .

Condition: New. pp. 232.

Paperback. Condition: Brand New. 278 pages. 9.00x6.00x0.75 inches. In Stock.

Condition: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.

Taschenbuch. Condition: Neu. IoT Machine Learning Applications in Telecom, Energy, and Agriculture | With Raspberry Pi and Arduino Using Python | Puneet Mathur | Taschenbuch | xv | Englisch | 2020 | Apress | EAN 9781484255483 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Condition: new. Questo è un articolo print on demand.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 296 pp. Englisch.

Condition: New. Print on Demand pp. 232.

Condition: New. PRINT ON DEMAND pp. 232.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers applying machine learning with the Internet of Things (IoT) in the agriculture, telecom, and energy sectors&nbspHelps create&nbspenterprise-scale applications using Raspberry Pi 3 B+ and Arduino Mega 2560 with Python.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 296 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.