TinyML Auto ML Deep Dive: Streaming Analytics for Edge Devices

Explore an in-depth tutorial on bringing streaming analytics to edge devices and microcontrollers using Stream Analyze's Auto ML platform. Learn about the end-to-end platform for developing edge AI solutions, combining real-time streaming analytics and on-device edge AI. Discover how this platform accelerates the process of bringing edge AI solutions to market, catering to data scientists, engineers, and domain experts without extensive coding skills. Dive into the Community Edition, Studio interface, and various tabs for normal settings and output windows. Gain hands-on experience with Raspberry Pi and Raspberry Pi Zero implementations. Follow along with a comprehensive demo covering sensor values, temperature and pressure readings, combining values into a single stream, and setting up streaming analytics to a monitoring center. Master MQTT client registration, listener setup, stream publishing, and data monitoring. Explore advanced concepts such as linear transformation, C2F function, and derivatives. Conclude with a model run-through and an informative Q&A session in this hour-long tinyML tutorial.

Introduction
About Stream Analyze
What is it used for
Community Edition
Studio
Studio Tabs
Normal Settings
Output Window
Raspberry Pi
Raspberry Pi Zero
Documentation
Demo
Sensor values
Temperature readings
Pressure readings
Combining values into single stream
Get readings function
Streaming analytics to a monitoring center
MQTT client registration
Setting up a listener
Publishing a stream
Reading the readings
Publishing the stream
Testing the stream
Monitoring the data
Linear transformation
C2F function
Derivative
Running the model
QA Session
Conclusion