Watch this Elektor Academy course anytime, anywhere. Pause and
rewind the course as needed. This course is approximately 01:47
minutes long. You can purchase the course via PayPal via either a
PayPal account or with a Debit or Credit Card. Contact
service@elektor.com if you have any questions after your purchase.
Course Description
Artificial intelligence (AI) and machine learning (ML) can seem
like incredibly challenging topics to get into. Most solutions
involve complex software and a cloud-based platform that performs
the learning. This course provides you with a simple and
understandable approach to using elementary ML. It only requires
your PC and a source-code neural network that works on Arduino and
other microcontrollers
In this course, you’ll learn about the basic building block of
ML, neural networks. After covering some of the history of its
development and what today’s AI is capable of, you’ll see how
artificial neurons learn basic capabilities through software
examples. With simple learned functionality, like replicating an
AND gate, behind us, we’ll learn why learning an XOR gate’s
functionality was challenging for early artificial neuron
approaches and how that challenge was overcome.
With this light touch on the theory complete, we’ll explore how
this simple little neuron can be used as part of an autonomous
driving system to detect the color of traffic lights. Until this
point, all the code demonstrated runs on a PC using Processing.
The final section shows how the same (lightly modified) code
runs on an Arduino to implement the same traffic light color
detecting application. Due to their limited performance,
microcontrollers take a long time to learn new capabilities. To
speed up learning, an approach for creating the “learned
capability” is provided by coupling the performance of your PC with
the Arduino.
After that, the world is your oyster! You’ll have a neural
network suited to execution on a microcontroller and a tool to
teach it new things for your own projects – who knows what you’ll
make..
Prerequisite knowledge
Before attending this class, we expect that you should:
- Know how to install and use the Arduino IDE.
- (Recommended) Know how to install and use Processing.
- Be able to build and execute example sketches.
- Can modify a sketch to create your own application.
- Understand C/C++ as used in Arduino.
Course Material
The course is delivered as a walk-through with demonstrations of
the examples covered. The code used in the course is available on
GitHub for use as the basis of your own sketches via this link:
https://github.com/ElektorLabs/ea0002-neuralnetwork-arduino