Using Google’s Colaboratory and Raspberry Pi for DIY Machine Learning Applications | #python #piday #raspberrypi @Raspberry_Pi
Building computation models in Colaboratory is quite intuitive and can be developed using a Raspberry Pi 3 B+. The Raspberry Pi 3 B+ has enough processing and wireless capabilities available to easily manage the machine learning applications built in Colaboratory: a 1.4GHz, 64-Bit quad-core ARM Cortex – A53 processor; dual-band wireless Local Area Network (LAN); and Bluetooth 4.2/ BLE features.
There are two toolbars in Colaboratory that provide the functionality features of the notebook. The first toolbar consists of File, Edit, View, Insert, Runtime, Tools, and Help. The second toolbar located below the first one has Code, Text, Cell(up), and Cell(down). The Hello Colaboratory website has a variety of example interactive notebooks to explore programming concepts, functions, and features. New code and text notebooks can be created by selecting these keywords in the second toolbar.
Upon selection of the document type, a blank notebook will be created and display on your computer monitor’s screen. I created a simple Python counter using the “for-loop” instruction. Also, a method of displaying or printing a range of numbers from the Python counter using the “list” instruction was implemented within Colaboratory notebook.
With the support of the iPython kernel supporting a variety of programming languages, data plots can be implemented by importing the matplotlib library. Python or a supporting programming language complements the graphical plotting feature.
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