Téléchargez le livre : IoT Machine Learning Applications in Telecom, Energy, and Agriculture

IoT Machine Learning Applications in Telecom, Energy, and Agriculture

With Raspberry Pi and Arduino Using Python

de

Éditeur :

Apress


Paru le : 2020-05-09



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
62,11 €
Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

badge apple Application Louise Reader
badge Android Application Louise Reader
Description

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.
Pages
278 pages
Collection
n.c
Parution
2020-05-09
Marque
Apress
EAN papier
9781484255483
EAN PDF
9781484255490
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
27
Taille du fichier
7496 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
62,11 €
EAN EPUB
9781484255490
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
27
Taille du fichier
11715 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
62,11 €

Suggestions personnalisées