It takes the average reader 4 hours and 48 minutes to read IoT Machine Learning Applications in Telecom, Energy, and Agriculture by Puneet Mathur
Assuming a reading speed of 250 words per minute. Learn more
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 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 scratch Who This Book Is For Raspberry Pi and Arduino enthusiasts and data science and machine learning professionals.
IoT Machine Learning Applications in Telecom, Energy, and Agriculture by Puneet Mathur is 284 pages long, and a total of 72,136 words.
This makes it 96% the length of the average book. It also has 88% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 6 hours and 34 minutes to read IoT Machine Learning Applications in Telecom, Energy, and Agriculture aloud.
IoT Machine Learning Applications in Telecom, Energy, and Agriculture is suitable for students ages 12 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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