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The open source code for the paper "Block Attention and Switchable Normalization based Deep Learning Framework for Segmentation of Retinal Vessels"

This repository is beginner-friendly for ML and contains all the codes related to the Course: Supervised Machine Learning Regression and Classification in Coursera

This project explores ML techniques across classification and regression. It includes penguin species classification, breast cancer prediction, and baseball performance prediction using regularization. After, I will develop an XGBoost model for hotel cancellation prediction, analyzing key booking factors and optimizing performance. (In Progress)

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Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng

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.

Implementation of necessary supervised machine learning algorithms for regression and classification.

This project applies regularization techniques (Ridge, Lasso, and Elastic Net) to improve real estate price forecasting. This project focuses on reducing overfitting and increasing the stability of regression models' predictions