Topic: "regularization-techniques"
ejikeugba/serp
Smooth Effects on Response Penalty for CLM
Language: R - Size: 1.01 MB - Last synced at: 1 day ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

onchipuis/Tests_A-Connect
Library for easy deployment of A-Connect methodology.
Language: Python - Size: 5.54 GB - Last synced at: 15 days ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

MohammedSaqibMS/Regularization
This repository implements a 3-layer neural network with L2 and Dropout regularization using Python and NumPy. It focuses on reducing overfitting and improving generalization. The project includes forward/backward propagation, cost functions, and decision boundary visualization. Inspired by the Deep Learning Specialization from deeplearning.ai.
Language: Jupyter Notebook - Size: 3.01 MB - Last synced at: about 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

surafiel-habib/Transformer-Based-Amharic-to-English-Machine-Translation-with-Character-Embedding-and-Combined-Regul
Language: Jupyter Notebook - Size: 9.04 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

harmanveer-2546/Guide-to-Regularization
Regularization is a crucial technique in machine learning that helps to prevent overfitting. Overfitting occurs when a model becomes too complex and learns the training data so well that it fails to generalize to new, unseen data.
Language: Jupyter Notebook - Size: 879 KB - Last synced at: 29 days ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0
