A comparison of runtimes to fit OLS regression models using different Python libraries (Scikit-learn, statsmodels, Numpy matrix multiplication)
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Updated
Mar 12, 2021 - Jupyter Notebook
A comparison of runtimes to fit OLS regression models using different Python libraries (Scikit-learn, statsmodels, Numpy matrix multiplication)
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.
ML sprint (OLS, KNN, scikit-learn) from Le Wagon Women in Machine Learning event.
Repository for SLR projects
For a real estate firm, building a house price prediction model based upon various factors. Problem - Regression | Algorithm used -Linear Regression using OLS
In this notebook we would be learning how to check that whether there is intercacion between two dependent variables or not. After that we would consider or add that interaction variable into our regression model and will monitor the changes in the parametrs.
Homework 1 for the INTL 601 Quantitative Research Methods Course, Prof. David Carlson, Koç University.
I used the New York Bike Counts dataset to formulate a hypothesis about the number of bikes crossing the Brooklyn Bridge. This dataset contains the number of bikes that crossed each bridge during each day. I first used this dataset to formulate a hypothesis and then used linear regression to test if my hypothesis was correct.
I perform a retrospective analysis on the linear regression analysis that I previously performed on the NYC Bike Counts dataset. Specifically, I analyze my linear regression analysis to identify anything that I could have done differently.
A collaborative project looking into the likelihood of Covid-19 infection in the United States.
This project is about statistically analyzing risk factors for heart disease and performing A/B testing, descriptive and inferential statistics to provide health care plans and strategies to better understand the risk factors assocaited with heart disease and give key insights into what factors contribute most heavily and least heavily to the de…
MITx - MicroMasters Program on Statistics and Data Science - Data Analysis: Statistical Modeling and Computation in Applications - First Project
Estimate the impact of OIL and USD towards CPI using least squares method using R
Applying econometric analyses based on a videogame consoles dataset, using statistical software (Stata) and evaluate the results.
Prediction-model-for-predicting-Price-of-Cars
Used libraries and functions as follows:
This is my final project for my master's degree in Data Analytics
Here I have checked and removed for heteroskedasticity .
This is a simple Excel file that explains thoroughly, all the steps to a Simple Linear Regression model via the OLS method. I use basic excel commands for matrix multiplication and matrix inversion. The input data are not drown from anywhere and are used as an example for the better understanding of the procedure.
Prediction of how much sales revenue expected from each customer with the website traffic data acquired from an online retailer that provides information on customer’s website visit behavior
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