mlnjsh/Loss-Functions-In-Detail
📐 Deep dive into Loss Functions — MSE, MAE, Cross-Entropy, Huber, Focal, Hinge & more. Math, intuition, code & visualizations.
15
/ 100
Experimental
No License
No Package
No Dependents
Maintenance
13 / 25
Adoption
1 / 25
Maturity
1 / 25
Community
0 / 25
Stars
1
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Mar 25, 2026
Commits (30d)
0
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
adobe/antialiased-cnns
pip install antialiased-cnns to improve stability and accuracy
66
HelmchenLabSoftware/Cascade
Calibrated inference of spiking from calcium ΔF/F data using deep networks
58
lucidrains/RIM-pytorch
Implementation of Recurrent Independent Mechanisms in Pytorch
55
orchardbirds/bokbokbok
Custom Loss Functions and Evaluation Metrics for XGBoost and LightGBM
53
KaiyangZhou/pytorch-center-loss
Pytorch implementation of Center Loss
51