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Linear regression provides a solid foundation for understanding data and making predictions. My next step is to find data train my model (This is currently a work in progress).\n\n## Overview:\nMy script is simple and written for a straightforward scenario with one feature. \n+ Import Libraries: We use numpy for array manipulation, LinearRegression from scikit-learn for modeling, and matplotlib for plotting.\n+ Data: X is the feature matrix, and y is the target vector.\n+ Create Model: LinearRegression() initializes the linear regression model.\n+ Fit Model: model.fit(X, y) trains the model using the provided data.\n+ Predict: model.predict(X) generates predictions based on the fitted model.\n+ Print Results: Displays the intercept and coefficient of the fitted line.\n+ Plot: Shows the data points and the fitted line using matplotlib.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstella4444%2Flinear-regression","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstella4444%2Flinear-regression","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstella4444%2Flinear-regression/lists"}