This repository contains a notebook that implements four types of deep neural networks. The neural networks implemented include: Feedforward Neural Network, a Convolutional NN, a Recurrent NN and, finally, the Transformer. Both the sequential (for FNN) and the functional (for the others) Keras API were used.
This project aims to use four types of deep neural networks to partition the sound of heart auscultation in its four phases: S1, systole, S2 and Dyastole. The short time Fourier transform was used in data preprocessing.
Contributing: We welcome contributions from the community! If you find any issues or have suggestions for improvements, please feel free to open an issue or submit a pull request. Your contributions will help make this tutorial even better for others.
License: This tutorial is provided under the MIT License, which allows you to use, modify, and distribute the code freely.
We hope you find this repository useful!