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feat: add tooltip explanations for complex ML/Neuro terminology #101

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16 changes: 8 additions & 8 deletions templates/index.html
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Expand Up @@ -759,7 +759,7 @@ <h4 class="card-title">ResNet-50 Classification</h4>
</div>
<div class="accuracy-badge teal">
<span class="acc-value">92%</span>
<span class="acc-label">Tversky</span>
<span class="acc-label" title="A metric that quantifies the similarity between predicted and ground truth segmentation">Tversky</span>
</div>
</div>
<div class="card-text-area">
Expand All @@ -770,9 +770,9 @@ <h4 class="card-title">ResUNet Segmentation</h4>
accurate localization.
</p>
<div class="card-tags">
<span class="tag teal">Encoder-Decoder</span>
<span class="tag sky">Skip Connections</span>
<span class="tag beige">Focal Tversky</span>
<span class="tag teal" title="A network architecture where an encoder extracts features and a decoder reconstructs the spatial resolution.">Encoder-Decoder</span>
<span class="tag sky" title="Connections in neural networks that skip some layers, helping the network learn identity functions and preserve spatial details.">Skip Connections</span>
<span class="tag beige" title="Loss function that helps handle class imbalance by penalizing false negatives.">Focal Tversky</span>
</div>
</div>
<div class="card-visual">
Expand Down Expand Up @@ -3398,11 +3398,11 @@ <h4>Technical Configuration</h4>
</div>
<div class="config-item">
<span class="config-label">Loss Function</span>
<span class="config-value">Focal Tversky Loss (α=0.7, β=0.3)</span>
<span class="config-value" title="Loss function that helps handle class imbalance by penalizing false negatives.">Focal Tversky Loss (α=0.7, β=0.3)</span>
</div>
<div class="config-item">
<span class="config-label">Optimizer</span>
<span class="config-value">Adam (lr=0.05, ε=0.1)</span>
<span class="config-value" title="An adaptive learning rate optimization algorithm.">Adam (lr=0.05, ε=0.1)</span>
</div>
<div class="config-item">
<span class="config-label">Activation (Output)</span>
Expand All @@ -3418,11 +3418,11 @@ <h5><i class="fas fa-chart-area"></i> Segmentation Metrics</h5>
<div class="output-items">
<div class="output-item">
<i class="fas fa-bullseye"></i>
<span>92% Tversky Index</span>
<span title="A metric that quantifies the similarity between predicted and ground truth segmentation">92% Tversky Index</span>
</div>
<div class="output-item">
<i class="fas fa-dice"></i>
<span>0.91 Dice Score</span>
<span title="A metric used to evaluate the similarity between the predicted segmentation and ground truth.">0.91 Dice Score</span>
</div>
<div class="output-item">
<i class="fas fa-percentage"></i>
Expand Down