A Machine Learning project to predict bike-sharing counts using regression models, including linear, polynomial, and regularized techniques
Explore various regression models including univariate and multivariate linear regression, along with regularization techniques such as Ridge Regression and Lasso Regression. This repository contains Jupyter Notebook files (.ipynb) demonstrating the implementation and usage of different regression models. Additionally, datasets used for training an
Logistic Regression with Ridge and Lasso
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