  With the enhancement of Machine Learning, many tools are being designed to
assist developers to easily create their Machine Learning models. In this
paper, we propose a novel method for auto creation of such custom models for
constraint devices using transfer learning without the need to write any
machine learning code. We share the architecture of our automatic model
creation tool and the CNN Model created by it using pretrained models such as
YAMNet and MobileNetV2 as feature extractors. Finally, we demonstrate accuracy
and memory footprint of the model created from the tool by creating an
Automatic Image and Audio classifier and report the results of our experiments
using Stanford Cars and ESC-50 dataset.
