Modeling GuidesΒΆ
The following documents describe the various modeling features provided by the MLTK.
For complete tutorials, please see the Tutorials.
Model Profiler - Provides information about how efficiently a model may run on an embedded target
Model Profiler Utility - Standalone model profiler executable with webpage interface
Model Visualizer - View an ML model in an interactive webpage
Model Specification - Specify everything needed to create, train, and evaluate a machine learning model
Model Training - Train a Machine Learning model using the MLTK and Google Tensorflow
Model Evaluation - Evaluate the accuracy of a trained model
Model Quantization - Reduce memory usage by compressing model weights
Model Parameters - Embed custom parameters into the generated model file
Model Summary - Generate a text summary of a model
Model Archive - Store model information in a distributable archive
Model Search Path - Configure how models are found by the MLTK commands and APIs