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.
Each Friday is PiDay here at Adafruit! Be sure to check out our posts, tutorials and new Raspberry Pi related products. Adafruit has the largest and best selection of Raspberry Pi accessories and all the code & tutorials to get you up and running in no time!
Adafruit publishes a wide range of writing and video content, including interviews and reporting on the maker market and the wider technology world. Our standards page is intended as a guide to best practices that Adafruit uses, as well as an outline of the ethical standards Adafruit aspires to. While Adafruit is not an independent journalistic institution, Adafruit strives to be a fair, informative, and positive voice within the community – check it out here: adafruit.com/editorialstandards
Stop breadboarding and soldering – start making immediately! Adafruit’s Circuit Playground is jam-packed with LEDs, sensors, buttons, alligator clip pads and more. Build projects with Circuit Playground in a few minutes with the drag-and-drop MakeCode programming site, learn computer science using the CS Discoveries class on code.org, jump into CircuitPython to learn Python and hardware together, TinyGO, or even use the Arduino IDE. Circuit Playground Express is the newest and best Circuit Playground board, with support for CircuitPython, MakeCode, and Arduino. It has a powerful processor, 10 NeoPixels, mini speaker, InfraRed receive and transmit, two buttons, a switch, 14 alligator clip pads, and lots of sensors: capacitive touch, IR proximity, temperature, light, motion and sound. A whole wide world of electronics and coding is waiting for you, and it fits in the palm of your hand.
Have an amazing project to share? The Electronics Show and Tell is every Wednesday at 7:30pm ET! To join, head over to YouTube and check out the show’s live chat and our Discord!