Publications by Taha Ahmad
DATA624 Brewing Mode
library(caret) library(tidyverse) Introduction New regulations are requiring us to understand our manufacturing process and the predictive factors with modeling. We also need to choose an optimal predictive model of PH to report to our boss. We have been given historical data regarding our manufacturing process that has already been split int...
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DATA622 Final Project
library(tidyverse) library(skimr) #skim library(gdata) #trim library(ggpubr) #ggarrange library(scales) #formatting numbers in ggplot axis library(cowplot) #density chart library(outliers) #scores library(qdapTools) #mtabulate library(ggcorrplot) #corrplot for categorical data library(correlationfunnel) library(...
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DATA624 Brewing Models Exploration
library(caret) library(tidyverse) Introduction New regulations are requiring us to understand our manufacturing process and the predictive factors with modeling. We also need to choose an optimal predictive model of PH to report to our boss. We have been given historical data regarding our manufacturing process that has already been split int...
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DATA621 Final SalPred
Introduction Our goal is to utilize job salary data (retrieved from Ask A Manager Salary Survey here: https://docs.google.com/spreadsheets/d/1IPS5dBSGtwYVbjsfbaMCYIWnOuRmJcbequohNxCyGVw/edit?resourcekey#gid=1625408792) and demographic data to predict if the salaries in the survey end up above or below per capita personal income for state. We ori...
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DATA622 Support Vector Machines
library(tidyverse) ## Warning: package 'ggplot2' was built under R version 4.3.2 ## Warning: package 'dplyr' was built under R version 4.3.2 ## Warning: package 'stringr' was built under R version 4.3.2 ## Warning: package 'lubridate' was built under R version 4.3.2 library(skimr) library(DataExplorer) library(corrplot) library(ggfortify) libra...
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DATA621 US Salary Predictions
Introduction Our goal is to utilize job salary data (retrieved from Ask A Manager Salary Survey here: https://docs.google.com/spreadsheets/d/1IPS5dBSGtwYVbjsfbaMCYIWnOuRmJcbequohNxCyGVw/edit?resourcekey#gid=1625408792) and demographic data to predict if the salaries in the survey end up above or below per capita personal income for state. We ori...
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DATA624 JK Chapter 8
library(tidyverse) library(caret) Introduction In this document, we will be going through exercises 8.1, 8.2, 8.3, and 8.7 from Applied Predictive Modeling - Kuhn and Johnson. Exercises 8.1 Recreate the simulated data from Exercise 7.2: library(mlbench) set.seed(200) simulated <- mlbench.friedman1(200, sd = 1) simulated <- cbind(simulated$x...
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DATA624 JK Chapter 7
library(tidyverse) library(caret) Introduction In this document, we will be going through exercises 7.2 and 7.5 from Applied Predictive Modeling - Kuhn and Johnson. Exercises 7.2 Friedman (1991) introduced several benchmark data sets create by sim- ulation. One of these simulations used the following nonlinear equation to create data: y = 10...
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DATA624 JK Chapter 6
library(tidyverse) library(elasticnet) library(caret) library(lars) library(pls) library(stats) library(corrplot) library(MASS) library(skimr) library(DataExplorer) library(cowplot) Introduction In this document, we will be going through exercises 6.2 and 6.3 from Applied Predictive Modeling - Kuhn and Johnson. Exercises 6.2 Developin...
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DATA 622 Decision Trees Algorithms
library(tidyverse) library(skimr) library(DataExplorer) library(corrplot) library(ggfortify) library(caret) set.seed(123) Introduction Our objective for this analysis is to make two decision trees with different variables used and a random forest model from a dataset to compare how the results change depending on which model we are using. ...
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