regularization-to-avoid-overfitting
There are 7 repositories under regularization-to-avoid-overfitting topic.
sabrid369/BFMD-SN-U-net
The open source code for the paper "Block Attention and Switchable Normalization based Deep Learning Framework for Segmentation of Retinal Vessels"
Sohoxic/Supervised-Machine-Learning-Regression-and-Classification
This repository is beginner-friendly for ML and contains all the codes related to the Course: Supervised Machine Learning Regression and Classification in Coursera
Md-Emon-Hasan/Machine-Learning-Specialization
Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng
maheera421/Supervised-Machine-Learning
Implementation of necessary supervised machine learning algorithms for regression and classification.
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.