+Comfortable querying large databases.
+
+Familiar with database design.
:::
::: {style="margin: 10px 20px 20px 10px; padding: 20px; background-color: rgb(230, 225, 225);"}
-#### Machine Learning
+## [Machine Learning](#machine-learning-1)
Familiar with Neural Networks (including CNN and RNN). Comfortable with XGBoost, RandomForest, Descision Trees, and Gradient Boosted Models. Very comfortable with all supervised learning.
@@ -95,7 +117,6 @@ Familiar with Neural Networks (including CNN and RNN). Comfortable with XGBoost,
::::
-
-
Hans Capener - Portfolio
+- HELLO! WELCOME TO MY PORTFOLIO! +
- READ ME: +
- Skill + Showcase +
- 1. Data Wrangling and
Visualization
-
@@ -1425,39 +1431,73 @@
- Senior, Data Science major, Brigham Young University-Idaho +
- Minoring in Mathematics and Statistics +
- Expected Graduation: April 2025 +
- Intend to pursue a master’s degree in Statistics, considering +further studies for a PhD. +
- The purpose of this website to display my capabilities gained from +personal projects, as well as school. It has been designed to +navigate quickly to whatever is of most interest of the viewer +by using the side bar on the left. +
- All of the code used to generate each graph on this +website can be made visible by clicking the small +“Code” button on the right side of the screen above each +visualization. +
- Some visualizations have full analyses papers +associated with them; click the links to see them if you are interested. +They will by highlighted red like this. +
- All of the code used to generate each of these graphs can be made -visible by clicking the small “Show” button on the right side of the -screen above each visualization. -
- Feel free to use the tabs on the left to navigate quickly to -whatever intrigues you the most. -
- Some visualizations have full analysis associated with them; click -the links to see them if you are interested. -
- Senior, Data Science major, Brigham Young University-Idaho +
- Minors in Mathematics and Statistics +
- Expected Graduation: April 2025 +
- Intend to pursue a master’s degree in Statistics, considering +further studies for a PhD. +
Hans Capener - Portfolio
-->HELLO! WELCOME TO MY PORTFOLIO!
--- +++-
- +- -+Hans Capener
+Education:
+-
+
Future Plans:
+-
+
--+Data Wrangling and Visualization
+
+++READ ME:
+-
+
+Skill Showcase
+ +++-Data Wrangling and +Visualization
I am adept with R(tidyverse) and Python(pandas and seaborn) for data wrangling and visualization.
-diff --git a/portfolio.Rproj b/portfolio.Rproj new file mode 100644 index 0000000..8e3c2eb --- /dev/null +++ b/portfolio.Rproj @@ -0,0 +1,13 @@ +Version: 1.0 + +RestoreWorkspace: Default +SaveWorkspace: Default +AlwaysSaveHistory: Default + +EnableCodeIndexing: Yes +UseSpacesForTab: Yes +NumSpacesForTab: 2 +Encoding: UTF-8 + +RnwWeave: Sweave +LaTeX: pdfLaTeX diff --git a/profile.jpg b/profile.jpg new file mode 100644 index 0000000..230c48f Binary files /dev/null and b/profile.jpg differ diff --git a/test.Rmd b/test.Rmd index 0686018..91c6f12 100644 --- a/test.Rmd +++ b/test.Rmd @@ -23,10 +23,39 @@ output: -:::: {style="display: grid; grid-template-columns: 1fr 1fr; grid-column-gap: 10px; text-align: center; padding=30px; background-color: rgb(245, 240, 240);"} +:::: {style="display: grid; grid-template-columns: 1fr 1fr; grid-column-gap: 10px; background-color: #9F2042; padding: 20px; margin: 0em -3.236em"} + +::: {style="margin:20px; padding: 20px:"} +Statistical Analysis
++-Statistical Analysis
I can create interpretable multiple linear regression models, as well as perform many other statistical tests.
-SQL
--Comfortable querying large databases. Familiar with database -design.
++-SQL
++Comfortable querying large databases.
+Familiar with database design.
-Machine Learning
+++Machine Learning
Familiar with Neural Networks (including CNN and RNN). Comfortable with XGBoost, RandomForest, Descision Trees, and Gradient Boosted @@ -2000,18 +2040,6 @@
Machine Learning
-->
--A couple things to note:
--
-
-1. Data Wrangling and Visualization
@@ -2158,22 +2186,23 @@Our World In Data
keyheight = 0.9, keywidth = 0)) + labs(title="Fruit consumption vs. GDP per capita, 2020", - subtitle="Average per capita fruit consumption, measured in kilograms per year versus\ngross domestic product (GDP) per capita, measured in constant international-$", - x="GDP per capita", - y="Fruit supply per person") + - theme_classic() + - theme( - panel.grid.major = element_line(linetype='dotted', color='gray70'), - axis.line.y = element_blank(), - axis.line.x = element_line(size=0.25), - axis.ticks.y = element_blank(), - axis.ticks.x = element_blank(), - legend.title = element_blank(), - legend.justification = c(1,1), - axis.title.x = element_text(vjust=-1), - axis.title.y = element_text(vjust=4) - )
+ subtitle="Average per capita fruit consumption, measured in kilograms per year versus + gross domestic product (GDP) per capita, measured in constant international-$", + x="GDP per capita", + y="Fruit supply per person") + + theme_classic() + + theme( + panel.grid.major = element_line(linetype='dotted', color='gray70'), + axis.line.y = element_blank(), + axis.line.x = element_line(size=0.25), + axis.ticks.y = element_blank(), + axis.ticks.x = element_blank(), + legend.title = element_blank(), + legend.justification = c(1,1), + axis.title.x = element_text(vjust=-1), + axis.title.y = element_text(vjust=4) + )
-Original Graph:
@@ -2241,7 +2270,6 @@Which airport is best?
best_airport.save("Python/best_airport.html",embed_options={'width': 400})DS250 2x Machine Learning x2
+:::
+
+::: {style="margin: 20px; padding: 10px 20px; background-color: rgb(230, 225, 225);"}
+
+## Personal Overview
+
+Education:
+
+- Senior, Data Science major, Brigham Young University-Idaho
+- Minors in Mathematics and Statistics
+- Expected Graduation: April 2025
+
+Future Plans:
+
+- Intend to pursue a master's degree in Statistics, considering further studies for a PhD.
+:::
+
+::::
+
+
+ +# Skill Showcase + +### *Click Titles* or use side nav bar + +:::: {style="display: grid; grid-template-columns: 1fr 1fr; grid-column-gap: 10px; text-align: center; padding=30px; background-color: rgba(159, 32, 66, 0.4);"} ::: {style="margin: 20px 10px 10px 20px; padding: 20px; background-color: rgb(230, 225, 225);"} -#### Data Wrangling and Visualization +## [Data Wrangling and Visualization](#data-wrangling-and-visualization-1)I am adept with R(tidyverse) and Python(pandas and seaborn) for data wrangling and visualization.@@ -34,14 +63,14 @@ I am adept with R(tidyverse) and Python(pandas and seaborn) for data wrangling a ::: {style="margin: 20px 20px 10px 10px; padding: 20px; background-color: rgb(230, 225, 225);"} -#### Statistical Analysis +## [Statistical Analysis](#statistical-analysis-1)I can create interpretable multiple linear regression models, as well as perform many other statistical tests.::: ::: {style="margin: 10px 10px 20px 20px; padding: 20px; background-color: rgb(230, 225, 225);"} -#### SQL +## [SQL](#sql-1)Comfortable querying large databases. @@ -50,7 +79,7 @@ Familiar with database design. ::: ::: {style="margin: 10px 20px 20px 10px; padding: 20px; background-color: rgb(230, 225, 225);"} -#### Machine Learning +## [Machine Learning](#machine-learning-1)Familiar with Neural Networks (including CNN and RNN). Comfortable with XGBoost, RandomForest, Descision Trees, and Gradient Boosted Models. Very comfortable with all supervised learning.diff --git a/test.html b/test.html index 9a03a2e..ee0b398 100644 --- a/test.html +++ b/test.html @@ -7,7 +7,7 @@ - +Hans Capener - Portfolio @@ -1288,12 +1288,15 @@Hans Capener - Portfolio
@@ -1309,30 +1312,56 @@Hans Capener - Portfolio
---Data Wrangling and Visualization
+++++
+++Personal Overview
+Education:
+-
+
Future Plans:
+-
+
++Skill Showcase
+ +++-Data Wrangling and +Visualization
I am adept with R(tidyverse) and Python(pandas and seaborn) for data wrangling and visualization.
-Statistical Analysis
++-Statistical Analysis
I can create interpretable multiple linear regression models, as well as perform many other statistical tests.
-SQL
++-SQL
Comfortable querying large databases.
Familiar with database design.
-+Machine Learning
++Machine Learning
Familiar with Neural Networks (including CNN and RNN). Comfortable with XGBoost, RandomForest, Descision Trees, and Gradient Boosted @@ -1341,6 +1370,7 @@
Machine Learning