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index.html
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<link rel="preconnect" href="https://fonts.googleapis.com" />
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
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<link href="https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@400;600;700&display=swap" rel="stylesheet" />
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The program has been meticulously trained on a diverse and extensive dataset, known as the HAM10000 dataset. This dataset consists of 10,015 dermatoscopic images of skin lesions, meticulously collected and manually annotated. It is a valuable resource that has played a pivotal role in training our skin cancer classification model.
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</p>
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<ul>
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<li>Objective: HAM
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<li>Task: Classification</li>
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<li>Modality: Colour Images</li>
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</ul>
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<link href="https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@400;600;700&display=swap" rel="stylesheet" />
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<title><strong>HAM10000 Classification</strong></title>
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</head>
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<body>
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<div class="container">
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The program has been meticulously trained on a diverse and extensive dataset, known as the HAM10000 dataset. This dataset consists of 10,015 dermatoscopic images of skin lesions, meticulously collected and manually annotated. It is a valuable resource that has played a pivotal role in training our skin cancer classification model.
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</p>
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<ul>
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<li>Objective: HAM 10000 Identification</li>
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<li>Task: Classification</li>
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<li>Modality: Colour Images</li>
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</ul>
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