Welcome to my blog! You can find an organized directory of my posts on this page.
New? Click here for an introduction.
Just for Fun
- [Ongoing] : Book Reviews!
- 3/13/20: Five things I learned from my first job out of college
- 3/10/20: Economics/Statistics projects from my undergraduate degree
- 3/08/20: A List of Favorites, circa 2017
Kaggle Data Science Competition Write-ups [GitHub]:
- 7/01/20: Tweet Sentiment Extraction (+ Python code)
- 5/18/20: House Prices: Advanced Regression Techniques
- 5/07/20: Titanic: Machine Learning from Disaster
Notes on predictive modeling and using the caret package in R; based on Applied Predictive Modeling by Kuhn and Johnson.
- 5/11/20: Introduction and Overview of Content
- 5/12/20: Data Pre-Processing
- 5/13/20: Model Tuning and Overfitting
- 5/18/20: Regression
Notes on statistical learning; based on Intro to Statistical Learning by James, Witten, Hastie, and Tibshirani.
- 4/21/20: An Introduction to Statistical Learning
- 4/22/20: Linear Regression
- 4/24/20: Classification
- 4/25/20: Resampling Methods
- 4/27/20: Linear Model Selection and Regularization
- 4/30/20: Moving Beyond Linearity
- 5/01/20: Tree-Based Methods
- 5/02/20: Support Vector Machines
- 5/04/20: Unsupervised Learning
Notes on using R for data science; based on R for Data Science by Grolemund and Wickham.
- 2/12/20: Basic Data Visualization in R
- 2/15/20: Basic Data Transformation in R
- 2/16/20: Basic Data Exploration in R
- 2/17/20: High-Level Data Wrangling in R: Imports, Pivots, and Joins
- 2/18/20: Data Wrangling in R: Strings
- 2/21/20: Data Wrangling in R: Factors
- 2/22/20: Data Wrangling in R: Dates and Times
- 2/24/20: Programming in R: Pipes, Functions, and Vectors
- 2/24/20: Programming in R: Iteration
- 2/28/20: Model Building in R
- 3/04/20: Creating Simple Documents with R Markdown
- 3/05/20: Graphing in R for Effective Communication