This project aims to develop a machine learning model for detecting and classifying oral cancer levels from images. It leverages a dataset sourced from Kaggle containing information relevant to oral cancer research.
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Install Dependencies: Ensure you have the necessary dependencies installed. You can install them using the provided
requirements.txt
file:pip install -r requirements.txt
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Kaggle API Credentials: Set up your Kaggle API credentials by replacing
'your_username'
and'your_api_key'
in the Python code with your Kaggle username and API key, respectively.
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Download Dataset: Run the provided Python script to download the dataset from Kaggle and extract it.
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Data Exploration: Explore the dataset using the loaded Pandas DataFrame. Analyze basic statistics, visualize data distributions, and understand the structure of the dataset.
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Model Development: Utilize machine learning techniques, such as convolutional neural networks (CNNs), to develop a model for oral cancer detection and classification.
oral_cancer_classification.ipynb
: Jupyter Notebook containing the Python code for data loading, preprocessing, analysis, and model development.requirements.txt
: File listing the required Python packages and their versions.dataset
: Directory containing the downloaded dataset from Kaggle.README.md
: This file providing an overview of the project.
This project is licensed under the MIT License.