Cross-Entropy Loss for Classification
Understand cross-entropy loss for classification: interactive demos of binary and multi-class CE, the -log(p) curve, softmax gradients, and focal loss.
15 min readConcept
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Losses
Explore machine learning concepts related to Losses. Clear explanations and practical insights.
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Concepts Found
Concepts Related to Losses
Contrastive Loss for Representation Learning
Understand contrastive loss for representation learning: interactive demos of InfoNCE, triplet loss, and embedding space clustering with temperature tuning.
8 min readConcept
Focal Loss: Focusing on Hard Examples
Learn focal loss for deep learning: down-weight easy examples, focus on hard ones. Interactive demos of gamma, alpha balancing, and RetinaNet.
9 min readConcept
KL Divergence in Machine Learning
Learn KL divergence for machine learning: measure distribution differences in VAEs, knowledge distillation, and variational inference.
7 min readConcept
MSE and MAE Loss Functions
Interactive guide to MSE vs MAE for regression: explore outlier sensitivity, gradient behavior, and Huber loss with visualizations.
8 min readConcept