Regression Techniques in Machine learning including topics from Assumption, Simple and Multiple Linear Regression. Both theory and python codes are included.
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Updated
Dec 11, 2021 - Jupyter Notebook
Regression Techniques in Machine learning including topics from Assumption, Simple and Multiple Linear Regression. Both theory and python codes are included.
We will design a predictive model to predict the full-load power output of the Combined Cycle Power Plant Dataset from UCI ML repository and evaluate the performance of the model.
Homework 1 for the INTL 601 Quantitative Research Methods Course, Prof. David Carlson, Koç University.
Using a linear regression method, we build a model to determine the relationship between independent and dependent variable, and then predict the sales. In the process, we will use a statistical point of view for validation.
In this project, we implement a linear regression model and its extensions on a student grades dataset to enhance performance. The workflow includes advanced EDA, data preprocessing, and assumption checks. Key steps: dataset overview, univariate and bivariate analysis, data preprocessing, model building(2nd degree,l1,l2,EN) and result visualization
A Multiple Linear Regression project used to predict ride fares to optimize revenue growth.
Regression Analysis project
Predicting Used Car Price with Linear Model
Linear Regression Project
Skript zur Videoreihe Regressionsdiagnostik in R
The project provides a Regression on the Insurance Prediction Data which shows the features of individuals, tuned using Ridge & Lasso.
Building a statistical model using wine dataset
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