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losses

Explore machine learning concepts related to losses. Clear explanations and practical insights.

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Concepts Related to losses

August 5, 2025

Cross-Entropy Loss

Understand cross-entropy loss for classification: interactive demos of binary and multi-class CE, the -log(p) curve, softmax gradients, and focal loss.

deep-learning losses optimization classification information-theory

9 min readConcept

January 31, 2025

Contrastive Loss

Understand contrastive loss for representation learning: interactive demos of InfoNCE, triplet loss, and embedding space clustering with temperature tuning.

deep-learning losses self-supervised representation-learning contrastive-learning

8 min readConcept

January 31, 2025

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.

deep-learning losses classification object-detection imbalanced-data

9 min readConcept

January 31, 2025

KL Divergence

Learn KL divergence for machine learning: measure distribution differences in VAEs, knowledge distillation, and variational inference with interactive visualizations.

deep-learning losses probability information-theory VAE

7 min readConcept

January 31, 2025

MSE and MAE Loss Functions

Interactive guide to MSE vs MAE for regression: explore outlier sensitivity, gradient behavior, and Huber loss with visualizations.

deep-learning losses regression optimization

8 min readConcept