Classify Radio Signals with PyTorch

In this 2-hour long guided-project course, you will load a pretrained state of the art model CNN and you will train in PyTorch to classify radio signals with input as spectogram images. The data that you will use, consists of spectogram images (spectogram is a representation of audio signals) and there are targets such as ( Squiggle, Noises, Narrowband, etc). Furthermore, you will apply spectogram augmentation for classification task to augment spectogram images. Moreover, you are going to create train and evaluator function which will be helpful to write training loop. Lastly, you will use best trained model to classify radio signals given any 2D Spectogram of radio signal input images

• Load pretrained CNN model
• Create training and evaluation functions for training loop
• Understand spectrogram augmentations

• Basic familiarity with software or workflow used
• Ability to follow step-by-step instructions in English