Train-MobileNet for TinyML

🔬 Project Overview

This code is a script for training an image classification model MobileNet using PyTorch. The code is structured to facilitate easy training, evaluation, and monitoring of a deep learning model for image classification. It allows for periodic saving of the model’s state and provides insights into the model’s performance through loss curves and accuracy metrics. The repo also contains a script which is designed to process time series data from CSV files and generate Continuous Wavelet Transform (CWT) spectrograms for each column in the data. It’s typically used for signal analysis, particularly in scenarios involving time-frequency representation of signals.

(For full source code, pin configurations, and implementation details, please view the GitHub repository using the button above).