MicroMod Machine Learning Carrier Board Hookup Guide
The MicroMod Machine Learning Carrier Board combines some of the features of our SparkFun Edge Board and SparkFun Artemis boards, but allows you the freedom to explore with any processor in the MicroMod lineup without the need for a central computer or web connection. Voice recognition, always-on voice commands, gesture, or image recognition are possible with TensorFlow applications. An on board accelerometer and Qwiic ports allow you even more flexibility.
Let's dive in, get a good look at what's available to us, and go over a few quick examples!
In addition to your Machine Learning carrier board, you'll need a processor board to get started. Here we use the Artemis Processor Board, but there are a number of others you can choose from.
SparkFun MicroMod SAMD51 ProcessorDEV-16791
SparkFun MicroMod Artemis ProcessorDEV-16401
You'll also need a USB-C cable to connect the Carrier to your computer and if you want to add some Qwiic breakouts to your MicroMod project you'll want at least one Qwiic cable to connect it all together. Below are some options for both of those cables:
SparkFun Qwiic Cable KitKIT-15081
USB 3.1 Cable A to C - 3 FootCAB-14743
Reversible USB A to C Cable - 2mCAB-15424
Along with a processor and the pertinent cables and accessories, if you want to take full advantage of the features of the Machine Learning Carrier Board, you will need a microSD card:
microSD Card - 16GB (Class 10)COM-15051
The SparkFun MicroMod ecosystem is a unique way to allow users to customize their project to their needs. Do you want to send your weather data via a wireless signal (eg. Bluetooth or WiFi)? There's a MicroMod processor for that. Looking to instead maximize efficiency and processing power? You guessed it, there's a MicroMod processor for that.
We also recommend taking a look through the following tutorials if you are not familiar with the concepts covered in them: