mlnjsh/Loss-Functions-In-Detail

📐 Deep dive into Loss Functions — MSE, MAE, Cross-Entropy, Huber, Focal, Hinge & more. Math, intuition, code & visualizations.

/ 100

Experimental

No License No Package No Dependents

Maintenance 13 / 25

Adoption 1 / 25

Maturity 3 / 25

Community 0 / 25

Stars

Forks

—

Language

Jupyter Notebook

License

—

Category

Last pushed

Mar 25, 2026

Commits (30d)

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mlnjsh/Loss-Functions-In-Detail"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

HelmchenLabSoftware/Cascade

Calibrated inference of spiking from calcium ΔF/F data using deep networks

adobe/antialiased-cnns

pip install antialiased-cnns to improve stability and accuracy

KaiyangZhou/pytorch-center-loss

Pytorch implementation of Center Loss

devsisters/pointer-network-tensorflow

TensorFlow implementation of "Pointer Networks"

kimhc6028/relational-networks

Pytorch implementation of "A simple neural network module for relational reasoning" (Relational Networks)