TensorFlow Lite for Microcontrollers Kit

Machine learning has come to the 'edge' - small microcontrollers that can run a very miniature version of TensorFlow Lite to do ML computations.

This kit is curated to dip your toes into machine learning waters with the following components:

• Adafruit PyBadge with SAMD51 Cortex M4F processor @ 120MHz, with display, speaker and buttons
• Electret Microphone Amplifier - MAX4466 with Adjustable Gain
• JST PH 3-Pin to Female Socket Cable - 200mm
• Lithium Ion Polymer Battery with Short Cable - 3.7V 350mAh

The kit uses the PyBadge as the edge processor - a credit card sized compact board powered by the ATSAMD51 with 512KB flash and 192KB RAM. It includes 2MB QSPI flash for file storage.

The microphone can be plugged into the ports at the bottom for micro speech recognition. Demos are available for recognizing word pairs such as "yes/no", "up/down", and "cat/dog".

Note: Some light soldering is required to attach the microphone headers onto the board.

Requires: Lithium Ion Polymer Battery with Short Cable - 3.7V 350mAh (not included).

PyBadge Features:

• ATSAMD51J19 @ 120MHz, 3.3V logic/power
• 512KB FLASH + 192KB RAM
• 2MB SPI Flash for assets
• 1.8" 160x128 Color TFT Display
• 8 Game/Control Buttons with silicone tops
• 5 NeoPixels
• Triple-axis accelerometer
• Light sensor, reverse-mounted
• Built-in buzzer mini-speaker
• Mono Class-D speaker driver (4-8 ohm, up to 2W)
• LiPoly battery port with built-in recharging (battery not included)
• USB port for charging, programming, and debugging
• Two female header strips with Feather-compatible pinout
• JST ports for NeoPixels, sensor input, and I2C
• Reset button and On-Off switch