# Tirth27/Skin-Cancer-Classification-using-Deep-Learning

<https://repo.masters-masters.com/repos/Tirth27/Skin-Cancer-Classification-using-Deep-Learning>

[Accueil](https://repo.masters-masters.com/) › [Tirth27](https://repo.masters-masters.com/owners/Tirth27) › [Skin-Cancer-Classification-using-Deep-Learning](https://repo.masters-masters.com/repos/Tirth27/Skin-Cancer-Classification-using-Deep-Learning)

Tirth27/Skin-Cancer-Classification-using-Deep-Learning, dépôt open source à 171 étoiles sur GitHub. Carte Prototype de RepoMasters. Langage : Jupyter Notebook.

| Champ | Valeur |
| --- | --- |
| Propriétaire | [Tirth27](https://repo.masters-masters.com/owners/Tirth27) |
| Étoiles | 171 |
| Forks | 55 |
| Langage | [Jupyter Notebook](https://repo.masters-masters.com/languages/jupyter-notebook) |
| Licence | MIT |
| Création | 2021 |
| Sujets | melanoma-diagnosis, keras-tensorflow, kaggle-competition, skin-lesion-image, skin-cancer, deep-learning, image-classification, medical-imaging, convolutional-neural-networks, computer-vision |
| Rang | [Prototype (100 à 249 ★)](https://repo.masters-masters.com/ranks/rush) |
| Voir sur GitHub | [Tirth27/Skin-Cancer-Classification-using-Deep-Learning](https://github.com/Tirth27/Skin-Cancer-Classification-using-Deep-Learning) |

## Fiche du dépôt

Classify Skin cancer from the skin lesion images using Image classification. The dataset for the project is obtained from the Kaggle SIIM-ISIC-Melanoma-Classification competition.

Rang des dépôts qui ont 100 à 249 ★ sur GitHub. Probabilité publiée par carte tirée : 70 %. Rareté : Commune.

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Données : GitHub · Illustration dessinée par RepoMasters à partir de l’identifiant du dépôt et de la couleur de son langage.