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REFACTOR CNN BREAST CANCER DETECTION TO VGG16
Descrição da oferta de emprego
I'm looking for a seasoned Deep Learning programmer who can turn my existing CNN-based breast cancer detection code to include the VGG16 model.
This will involve.
- Complete refactoring of the code.
- Implementation in Python using both TensorFlow and Keras.
- Creating detailed comments to provide robust explanation and understanding of the code.
Max Budget--> Min Requirement --> An equivalent implementation using any of VGG16 or VGG19.
Link of the Project.
[login to view URL] The ideal candidate for this job would possess extensive experience in Neural Networks especially in VGG models, Python, TensorFlow, and Keras.
Understanding of breast cancer detection methods would also be beneficial.
I'm seeking a professional who can provide quality assurance, and ensure the refurbished code remains functional and understandable.
Python Machine Learning (ML) ID do Projeto.
# Sobre o projeto 18 propostas Aberto para ofertas Projeto remoto Ativo em 29 minutos atrás
This will involve.
- Complete refactoring of the code.
- Implementation in Python using both TensorFlow and Keras.
- Creating detailed comments to provide robust explanation and understanding of the code.
Max Budget--> Min Requirement --> An equivalent implementation using any of VGG16 or VGG19.
Link of the Project.
[login to view URL] The ideal candidate for this job would possess extensive experience in Neural Networks especially in VGG models, Python, TensorFlow, and Keras.
Understanding of breast cancer detection methods would also be beneficial.
I'm seeking a professional who can provide quality assurance, and ensure the refurbished code remains functional and understandable.
Python Machine Learning (ML) ID do Projeto.
# Sobre o projeto 18 propostas Aberto para ofertas Projeto remoto Ativo em 29 minutos atrás
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Detalhes da oferta
Empresa
- Indeterminado
Localidade
- Em todo Portugal
Endereço
- Indeterminado - Indeterminado
Data de publicação
- 12/04/2024
Data de expiração
- 11/07/2024
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