https://github.com/max-artis-11/deep-neural-network-for-breast-cancer-classification
Build and train a neural network with PyTorch to classify breast cancer tumors as benign or malignant using the Breast Cancer Wisconsin (Diagnostic) dataset. This project is part of the IBM Deep Learning with PyTorch course on Coursera.
https://github.com/max-artis-11/deep-neural-network-for-breast-cancer-classification
ai breast-cancer machine-learning python pytorch
Last synced: 3 months ago
JSON representation
Build and train a neural network with PyTorch to classify breast cancer tumors as benign or malignant using the Breast Cancer Wisconsin (Diagnostic) dataset. This project is part of the IBM Deep Learning with PyTorch course on Coursera.
- Host: GitHub
- URL: https://github.com/max-artis-11/deep-neural-network-for-breast-cancer-classification
- Owner: Max-Artis-11
- License: mit
- Created: 2025-04-18T16:29:12.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-04-18T16:47:46.000Z (7 months ago)
- Last Synced: 2025-04-23T23:46:57.277Z (6 months ago)
- Topics: ai, breast-cancer, machine-learning, python, pytorch
- Language: Jupyter Notebook
- Homepage:
- Size: 173 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Deep-Neural-Network-for-Breast-Cancer-Classification
# Neural Network for Breast Cancer Classification
Build and train a neural network with PyTorch to classify breast cancer tumors as benign or malignant using the Breast Cancer Wisconsin (Diagnostic) dataset. This project is part of the IBM Deep Learning with PyTorch course on Coursera: this project walks you through the complete process—from loading data to evaluating a model—using clear, well-commented code. I think its very ideal for those new to PyTorch and neural networks.
## Dataset: Breast Cancer Wisconsin (Diagnostic)
- 569 samples
- 30 numerical features
- 2 classes: `benign` and `malignant`
- Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
## Technologies
- Python
- PyTorch
- Jupyter Notebook
- Pandas, NumPy, Matplotlib
## What You'll Learn
- Load and preprocess real-world data
- Build and train a neural network with PyTorch
- Evaluate model accuracy and visualize performance
## Files
- `Breast_Cancer_Classification.ipynb` – Main notebook with code and explanations
- `README.md` – Project overview
## Acknowledgements
Developed as part of the [IBM Deep Learning with PyTorch](https://www.coursera.org/learn/deep-neural-networks-with-pytorch) course on Coursera using the Skills Network Labs environment.
## Setup Instructions
To run this project locally:
1. **Clone the repository**
```bash
git clone https://github.com/your-username/breast-cancer-classification.git
cd breast-cancer-classification
2. **Create a virtual environment (optional but recommended)**
```Terminal
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
4. **Install dependencies**
```Terminal
pip install -r requirements.txt
or
pip install torch pandas numpy matplotlib scikit-learn
6. **Launch Notebook or Colab**
```Terminal
jupyter notebook