Used libraries and functions as follows:
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Updated
Sep 12, 2022 - Jupyter Notebook
Used libraries and functions as follows:
Prediction of Delivery Time of newspapers using Sorting Time
Multi_Linear_Regression_on_Cars_data_to_predict_MPG
The given dataset contains electricity consumer household information. This information has been used to predict the amount to be paid by the consumer with the help of regression model selection and validated with feature importance.
Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in t
Prediction-model-for-predicting-Price-of-Cars
Prediction of Salary of individuals based on years of experience
Detailed implementation of various regression analysis models and concepts on real dataset.
Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. Consider only the below columns and prepare a prediction model for predicting Price. Corolla<-Corolla[c("Price","Age_
MLR assignment
This repository contains notebook introducing reader to basic concepts of multilinear regression and its application.
Used libraries and functions as follows:
Feasibility of staring a Sunday edition for a large Metroplitan newsapaper
Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Levera…
Prediction model for profit of 50_startups data
Supervised-ML---Multiple-Linear-Regression---Toyota-Cars. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-buil…
Predicting wage in the uswage dataset (Linear Regression). Model Selection, Model Diagnostics etc.
Business Case : The Waist Circumference - Adipose Tissue
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.p
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