MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03228nam a22002537a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
230221s2020 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781484255483 |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| ISSN-L |
9781484255483 |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
English |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
004 |
| Item number |
MAT |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Mathur, Puneet |
| Relator term |
author |
| 9 (RLIN) |
673951 |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
IoT Machine Learning Applications in Telecom Energy and Agriculture with Raspberry Pi and Arduino Using Python<br/><br/> |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Bangalore : |
| Name of publisher, distributor, etc. |
Apress, |
| Date of publication, distribution, etc. |
c2020 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XV, 278 p. |
| Other physical details |
: ill |
| 500 ## - GENERAL NOTE |
|---|
| General note |
About the author<br/><br/>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.<br/> |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes Index |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
SUMMARY:<br/>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. <br/><br/>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. <br/><br/>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. <br/><br/> What You Will Learn<br/><br/> Implement machine learning with IoT and solve problems in the telecom, agriculture, and energy sectors with Python<br/> Set up and use industrial-grade IoT products, such as Modbus RS485 protocol devices, in practical scenarios<br/> Develop solutions for commercial-grade IoT or IIoT projects<br/> Implement case studies in machine learning with IoT from scratch<br/><br/>Who This Book Is For<br/><br/>Raspberry Pi and Arduino enthusiasts and data science and machine learning professionals. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
158157 |
| Topical term or geographic name entry element |
Internet of Things |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
673952 |
| Topical term or geographic name entry element |
Machine Learning Computers Hardware |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
797 |
| Topical term or geographic name entry element |
Computer Input Output Equipment |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
TOC |
| Uniform Resource Identifier |
<a href="https://eaklibrary.neduet.edu.pk:8443/catalog/bk/books/toc/9781484255483.pdf">https://eaklibrary.neduet.edu.pk:8443/catalog/bk/books/toc/9781484255483.pdf</a> |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
WEB LINK |
| Uniform Resource Identifier |
<a href="https://link.springer.com/book/10.1007/978-1-4842-5549-0 ">https://link.springer.com/book/10.1007/978-1-4842-5549-0 </a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |
