Last Updated or created 2024-04-03

A while ago I bought a little machine learning kit.

I’ve been reading at listening to ML podcasts and websites.

One on Spotify I liked was:

Also, the following Coursera was interesting
https://www.coursera.org/learn/machine-learning

I’ve been testing using Python on my Laptop.
(see other posts)

And a camera with esp32 using face detection.

See here multiple posts about these experiments.

https://www.henriaanstoot.nl/tag/machinelearning/

Today the first experiments using this kit.

• Arduino Nano 33 BLE Sense board
• OV7675 Camera
• Arduino Tiny Machine Learning Shield
• USB A to Micro USB Cable
• 9 axis inertial sensor: what makes this board ideal for wearable devices
• humidity, and temperature sensor: to get highly accurate measurements of the environmental conditions
• barometric sensor: you could make a simple weather station
• microphone: to capture and analyse sound in real time
• gesture, proximity, light color and light intensity sensor : estimate the room’s luminosity, but also whether someone is moving close to the board
• Microcontroller nRF52840
• Operating Voltage 3.3V
• Input Voltage (limit) 21V
• DC Current per I/O Pin 15 mA
• Clock Speed 64MHz
• CPU Flash Memory 1MB (nRF52840)
• SRAM 256KB (nRF52840)
• EEPROM none
• Digital Input / Output Pins 14
• PWM Pins all digital pins
• UART 1
• SPI 1
• I2C 1
• Analog Input Pins 8 (ADC 12 bit 200 ksamples)
• Analog Output Pins Only through PWM (no DAC)
• External Interrupts all digital pins
• LED_BUILTIN 13
• USB Native in the nRF52840 Processor
• IMU LSM9DS1 (datasheet)

I just started and will update this page, with other experiments.

Note: displaying Arduino output without installing the IDE

stty -F /dev/ttyACM0 raw 9600
cat /dev/ttyACM0

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