Using multiple linear regression model to predict customer demand in order to make business decision
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Updated
Feb 23, 2022 - Jupyter Notebook
Using multiple linear regression model to predict customer demand in order to make business decision
This project calculates the equation of the line of best fit of a given correlation
Functional specification to calculate per country's happiness score
Complete mathematical and statistical analysis of linear regression model
Statistical analysis to predict the importance of various manufacturing parameters on fuel economy of a prototype car.
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project to predict smartphone sales based on the marketing budget spent on advertising using three platforms involves collecting data on marketing spending and smartphone sales, and using statistical and machine learning techniques to build a model that can predict future smartphone sales based on changes in marketing budget.
Predicting annual highest of sneakers on StockX
Business Goal: To model the demand for shared bikes with the available independent variables. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the business strategy to meet the demand levels and meet the customer's expectations.
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The project involves the multivariate regression analysis of a dataset.
developing several models (Linear Regression, Multiple Linear Regression, and Polynomial Regression) that will predict the price of the car using the variables or features. Then evaluating these models (in-sample, and cross-validation) using R-squared and Mean-Squared-Error metrics to find out which model is a better fit for this dataset.
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Performing multiple linear regression on a simple dataset.
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