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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

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Regression Models

Welcome to the Regression Models repository! This repository contains various regression models, including univariate and multivariate linear regression, as well as regularization techniques.

Contents

  • Regression_models: This folder contains Colab Notebook files (.ipynb) that demonstrate the implementation and usage of different regression models.

  • datasets: The datasets used for training and testing the regression models are stored in this folder.

Regression Models

  1. Linear Regression:

    • Implementation of univariate linear regression.
    • Implementation of multivariate linear regression.
  2. Regularization:

    • Implementation of regularization techniques such as Ridge Regression and Lasso Regression.

Getting Started

To get started with using the regression models in this repository:

  1. Clone the repository to your local machine:
    https://github.com/pavanreddy2307/Regression_models.git

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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

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