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Data science with Raspberry Pi = rea...

Kadhar, K. Mohaideen Abdul.

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Data science with Raspberry Pi = real-time applications using a localized cloud /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data science with Raspberry Pi/ by K. Mohaideen Abdul Kadhar, G. Anand.
其他題名:	real-time applications using a localized cloud /
作者:	Kadhar, K. Mohaideen Abdul.
其他作者:	Anand, G.
出版者:	Berkeley, CA :Apress : : 2021.,
面頁冊數:	xx, 239 p. :ill., digital ;24 cm.
內容註:	Chapter 1: Introduction to Data Science -- Chapter 2: Basics of Python Programming -- Chapter 3: Introduction to Raspberry Pi -- Chapter 4: Sensors and Signals -- Chapter 5: Preparing the Data -- Chapter 6: Visualizing the Data -- Chapter 7: Analysing the Data -- Chapter 8: Learning From Data -- Chapter 9: Case Studies.
Contained By:	Springer Nature eBook
標題:	Raspberry Pi (Computer) -
電子資源:	https://doi.org/10.1007/978-1-4842-6825-4
ISBN:	9781484268254

Data science with Raspberry Pi = real-time applications using a localized cloud /
Kadhar, K. Mohaideen Abdul.

Data science with Raspberry Pireal-time applications using a localized cloud /[electronic resource] :by K. Mohaideen Abdul Kadhar, G. Anand. - Berkeley, CA :Apress :2021. - xx, 239 p. :ill., digital ;24 cm.

Chapter 1: Introduction to Data Science -- Chapter 2: Basics of Python Programming -- Chapter 3: Introduction to Raspberry Pi -- Chapter 4: Sensors and Signals -- Chapter 5: Preparing the Data -- Chapter 6: Visualizing the Data -- Chapter 7: Analysing the Data -- Chapter 8: Learning From Data -- Chapter 9: Case Studies.

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. You will: Interface the Raspberry Pi with sensors Set up the Raspberry Pi as a localized cloud Tackle data science concepts with Python on the Pi.

ISBN: 9781484268254

Standard No.: 10.1007/978-1-4842-6825-4doiSubjects--Topical Terms:

2068775
Raspberry Pi (Computer)

LC Class. No.: QA76.8.R15 / K33 2021

Dewey Class. No.: 005.133

Data science with Raspberry Pi = real-time applications using a localized cloud /
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520 $a 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. You will: Interface the Raspberry Pi with sensors Set up the Raspberry Pi as a localized cloud Tackle data science concepts with Python on the Pi.
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