Linear-Regression-from-Scratch and Linear-Regression-From-Scratch
These are competitors—both implement linear regression with gradient descent from scratch in Python, targeting the same learning objective with overlapping functionality, so a user would select one based on preference for either the custom implementation approach (A) or the Jupyter Notebook walkthrough format (B).
About Linear-Regression-from-Scratch
mahdi-eth/Linear-Regression-from-Scratch
This project implements a Python-based linear regression model from scratch, complete with custom functions for mean squared error and gradient descent algorithm. It is tested on data, using features to predict target variables. The project offers a practical introduction to linear regression.
This project helps data scientists and machine learning engineers understand the core mechanics of linear regression by providing a transparent, from-scratch implementation. You provide a dataset with numerical features and a target variable, and it outputs a model that can predict future values, along with an explanation of how the predictions are made. It's ideal for those learning or teaching the foundational algorithms of predictive modeling.
About Linear-Regression-From-Scratch
raun1997/Linear-Regression-From-Scratch
This repo houses a Jupyter Notebook which is intended to walk you through Gradient Descent Algorithm from scratch.
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