The following tutorials provide end-to-end guides on how to develop machine learning model using the MLTK:

Name Description
Keyword Spotting - On/Off Develop an ML model to detect the keywords: "on" or "off"
Keyword Spotting - Pac-Man Develop a demo to play the game Pac-Man in a web browser using the keywords: "Left", "Right", "Up", "Down", "Stop", "Go"
Image Classification - Rock/Paper/Scissors Develop an image classification ML model to detect the hand gestures: "rock", "paper", "scissors"
Model Training in the "Cloud" Vastly improve model training times by training a model in the "cloud" using vast.ai
Model Optimization for MVP Hardware Accelerator Use the various MLTK tools to optimize a model to fit within an embedded device's resource constraints
Keyword Spotting with Transfer Learning Use a pre-trained model to quickly train a new model that detects the keywords: "one", "two", "three", "four"
Fingerprint Authentication Use ML to generate unique signatures from images of fingerprints to authenticate users
ONNX to TF-Lite Model Conversion Describes how to convert an ONNX formatted model file to the .tflite model format required by embedded targets