Welcome to IA_Deep_Learning! This repository showcases a project focused on solving real-world problems using deep learning techniques, specifically through a FEED-FORWARD model. Here's what you need to know:
- Domain: Deep Learning, Artificial Intelligence
- Language: Python
- Frameworks: TensorFlow, Keras
- Purpose: To classify cardiovascular diseases and images using a feed-forward neural network.
- Cardiovascular Disease Classification: Utilizes a feed-forward model to predict the presence of cardiovascular diseases based on patient data.
- Image Classification: Applies the same model architecture to classify images, demonstrating the versatility of feed-forward networks.
- Data Preprocessing: Includes steps for data cleaning, normalization, and feature engineering to prepare datasets for model training.
- Model Evaluation: Provides metrics and visualizations to assess model performance, including accuracy, precision, recall, and F1-score.
- Clone the Repository: git clone https://github.com/Ornella-Gigante/IA_Deep_Learning.git
text
- Setup Environment:
- Ensure you have Python installed.
- Install required libraries using
pip install -r requirements.txt.
- Run the Project:
- Navigate to the project directory.
- Execute the main script to train and evaluate the model.
- Experiment and Modify:
- Adjust the model architecture, hyperparameters, or dataset to explore different scenarios or improve performance.
This project is an excellent resource for:
- Deep Learning: Understand how feed-forward neural networks work and their applications in real-world problems.
- Data Science: Learn about data preprocessing, feature selection, and model evaluation techniques.
- Python Programming: Enhance your Python skills by working with deep learning libraries.
Feel free to:
- Fork the repository and make your own changes or improvements.
- Contribute by submitting pull requests with new features, bug fixes, or enhancements.
- Report Issues if you encounter any problems or have suggestions for the project.
- Ornella Gigante - Creator and Maintainer
This project is open-sourced under the MIT License. You are free to use, modify, and distribute the code as per the license terms.
Let's tackle real-world problems with the power of deep learning! 🎉