Publications by Nguyen Bui
Tune random forests for IKEA
This is the latest in my series of screencasts demonstrating how to use the tidymodels packages, from starting out with first modeling steps to tuning more complex models. Today’s screencast walks through how to get started quickly with tidymodels via usemodels functions for code scaffolding and generation, using this week’s #TidyTuesday data...
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Churn Analysis - Olist
setwd('C:/Users/DellPC/Desktop/Corner/Py_source_code/Project/Olist') htmltools::includeHTML('E-commerce Churn Analysis.html') E-commerce Churn Analysis In [1]: import numpy as np import pandas as pd import seaborn as sns sns.set(style = 'ticks') import matplotlib.pyplot as plt import matplotlib.dates as mdates import matplotlib.tick...
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Tune and interpret decision trees for wind turbines
Tune and interpret decision trees for wind turbines This is the latest in my series of screencasts demonstrating how to use the tidymodels packages, from starting out with first modeling steps to tuning more complex models. Today’s screencast walks through how to tune, fit and predict from decision tree models, using this week’s dataset on ...
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Olist in Marketing Sense
library(tidyverse) ## -- Attaching packages ------- tidyverse 1.3.0 -- ## v ggplot2 3.3.2 v purrr 0.3.4 ## v tibble 3.0.3 v dplyr 1.0.0 ## v tidyr 1.1.0 v stringr 1.4.0 ## v readr 1.3.1 v forcats 0.5.0 ## -- Conflicts ---------- tidyverse_conflicts() -- ## x dplyr::filter() masks stats::filter() ## x dplyr::lag() ...
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Map_Viz_Training
setwd('C:/Users/DellPC/Desktop/Corner/Py_source_code/Project/Olist') library(htmltools) includeHTML('map.html') ...
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Explore Art Media Over Time
Explore art media over time in the Tate collection dataset Explore the data Our modeling goal is to understnad how the media used to create artwork in the Tate collection has changed over time. Let’s start by reading in the data. library(tidyverse) ## -- Attaching packages -------- ## v ggplot2 3.3.2 v purrr 0.3.4 ## v tibble 3.0.3 ...
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Tidymodel for IKEA price
setwd('C:/Users/DellPC/Desktop/Corner/R_source_code') #registerDoParallel(4) Explore the data Our modeling goal is to predict the price of IKEA furniture from other furniture characteristics like category and size. library(tidyverse) ## -- Attaching packages -------- ## v ggplot2 3.3.2 v purrr 0.3.4 ## v tibble 3.0.3 v dplyr 1.0....
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Olist Ecommerce Visualization
Olist a Brazilian e-commerce Olist’s Business Model Olist is a Brazilian department store (marketplace) that operates in e-commerce segment, but is not an e-commerce itself as she says. It operates as a SaaS (Software as a Service) technology company since 2015. It offers a marketplace solution (of e-commerce segment) to shopkeepers of all s...
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Student Debt
This is the latest in my series of screencasts demonstraing how t ouse the tidymodels packages, from starting out with first modeling steps to tuning more complex models. Explore the data Our modeling goal is to understand how student debt and inequality has been changing over time. We can build a model to understand the relationship between stu...
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UN voting data
Explore data This analysis is very similar to what I did last May for tidyTuesday data set on cocktail recipes, so take a look at both to see what is the same and what is different for the 2 different datasets. Our modeling goal is to use unsupervised algorithms for dimensionality reduction with UN voting data to understand which countries are si...
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