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.

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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: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

ejikeugba/serp

Smooth Effects on Response Penalty for CLM

Language: R - Size: 1.01 MB - Last synced at: 4 days ago - Pushed at: 7 months ago - Stars: 1 - 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.

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onchipuis/Tests_A-Connect

Library for easy deployment of A-Connect methodology.

Language: Python - Size: 5.54 GB - Last synced at: about 2 months ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0