Nicht aus der Schweiz? Besuchen Sie lehmanns.de
Data Science with Raspberry Pi - K. Mohaideen Abdul Kadhar, G. Anand

Data Science with Raspberry Pi (eBook)

Real-Time Applications Using a Localized Cloud
eBook Download: PDF
2021 | 1st ed.
XX, 239 Seiten
Apress (Verlag)
978-1-4842-6825-4 (ISBN)
Systemvoraussetzungen
62,99 inkl. MwSt
(CHF 61,50)
Der eBook-Verkauf erfolgt durch die Lehmanns Media GmbH (Berlin) zum Preis in Euro inkl. MwSt.
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

Implement real-time data processing applications on the Raspberry Pi. This book uniquely helps you work with data science concepts as part of real-time applications using the Raspberry Pi as a localized cloud.  

You'll start with a brief introduction to data science followed by a dedicated look at the fundamental concepts of Python programming. Here you'll install the software needed for Python programming on the Pi, and then review the various data types and modules available. The next steps are to set up your Pis for gathering real-time data and incorporate the basic operations of data science related to real-time applications. You'll then combine all these new skills to work with machine learning concepts that will enable your Raspberry Pi to learn from the data it gathers. Case studies round out the book to give you an idea of the range of domains where these concepts can be applied. 

By the end of Data Science with the Raspberry Pi, you'll understand that many applications are now dependent upon cloud computing. As Raspberry Pis are cheap, it is easy to use a number of them closer to the sensors gathering the data and restrict the analytics closer to the edge. You'll find that not only is the Pi an easy entry point to data science, it also provides an elegant solution to cloud computing limitations through localized deployment.

What You Will Learn

  • Interface the Raspberry Pi with sensors
  • Set up the Raspberry Pi as a localized cloud
  • Tackle data science concepts with Python on the Pi

    Who This Book Is For

    Data scientists who are looking to implement real-time applications using the Raspberry Pi as an edge device and localized cloud. Readers should have a basic knowledge in mathematics, computers, and statistics. A working knowledge of Python and the Raspberry Pi is an added advantage.



    Dr. K. Mohaideen Abdul Kadhar has an undergraduate degree in electronics and communication engineering and an MTech with a specialization in control and instrumentation. In 2015, he obtained his PhD in control system design using evolutionary algorithms. He has more than 14 years of experience in teaching and research. His area of interest is implementing signal processing and control system concepts with Python programming on the Raspberry Pi. He has conducted many courses and delivered workshops in data science with Python programming. He has also acted as consultant for many industries in developing machine vision systems for industrial applications.

    Mr. G Anand obtained his BE degree in electronics and communication engineering in 2008, and his ME in communication systems in the year 2011. He has more than nine years of teaching experience with specialization in signal and image processing. He has handled courses and acted as the primary resource person in workshops related to Python programming. His current research focuses on artificial intelligence and machine learning.
    Implement real-time data processing applications on the Raspberry Pi. This book uniquely helps you work with data science concepts as part of real-time applications using the Raspberry Pi as a localized cloud.  You ll start with a brief introduction to data science followed by a dedicated look at the fundamental concepts of Python programming. Here you ll install the software needed for Python programming on the Pi, and then review the various data types and modules available. The next steps are to set up your Pis for gathering real-time data and incorporate the basic operations of data science related to real-time applications. You ll then combine all these new skills to work with machine learning concepts that will enable your Raspberry Pi to learn from the data it gathers. Case studies round out the book to give you an idea of the range of domains where these concepts can be applied. By the end of Data Science with the Raspberry Pi, you ll understand that many applications are now dependent upon cloud computing. As Raspberry Pis are cheap, it is easy to use a number of them closer to the sensors gathering the data and restrict the analytics closer to the edge. You ll find that not only is the Pi an easy entry point to data science, it also provides an elegant solution to cloud computing limitations through localized deployment.What You Will Learn Interface the Raspberry Pi with sensors Set up the Raspberry Pi as a localized cloud Tackle data science concepts with Python on the Pi Who This Book Is ForData scientists who are looking to implement real-time applications using the Raspberry Pi as an edge device and localized cloud. Readers should have a basic knowledge in mathematics, computers, and statistics. A working knowledge of Python and the Raspberry Pi is an added advantage.
    Erscheint lt. Verlag 24.6.2021
    Zusatzinfo XX, 239 p. 83 illus.
    Sprache englisch
    Themenwelt Informatik Weitere Themen Hardware
    Schlagworte Data Science • Localized Cloud • Pi • Python • Raspberry Pi
    ISBN-10 1-4842-6825-3 / 1484268253
    ISBN-13 978-1-4842-6825-4 / 9781484268254
    Haben Sie eine Frage zum Produkt?
    PDFPDF (Wasserzeichen)
    Größe: 5,4 MB

    DRM: Digitales Wasserzeichen
    Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

    Dateiformat: PDF (Portable Document Format)
    Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

    Systemvoraussetzungen:
    PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
    eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
    Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

    Buying eBooks from abroad
    For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

    Mehr entdecken
    aus dem Bereich