Solving the Monty Hall Problem
Learning Data Science
The blog posts below are structured as full Jupyter notebooks that will serve as a reference for myself and anyone else who is interested. Each post is a mini-project uses real world datasets that focuses on a learning a particular concept in data science. In addition, I included comments showing my thought process and what I personally learned from each project. The newer the post, the more knowledge I personally have in data science.
Bootstrap Confidence Intervals and Permutation Hypothesis Testing
Chi-Squared Test for Independence in Python
Hypothesis Testing with ANOVA in Python
Hypothesis Testing with Welch's t-test in Python
The Normal Distribution and the Central Limit Theorem - Applications to Data Science
Understanding Dispersion
Understanding Central Tedency
Business Oriented Data Analysis with SQL and Python
Cross Validation Methods for Machine Learning
Scraping Reddit Data to a Pandas Dataframe
Predicting Titanic Survivors with Machine Learning
Spark Dataframes and Spark SQL in Python
Working with Spark in Python
Predicting Bike Rentals with Decision Trees
Predicting House Prices with Linear Regression
Predicting Car Prices with K-Nearest Neighbors
Analyzing Jeopardy Data
Comparing Movie Review Websites
Creating Relations in SQL
Preparing Data for SQLite
Analyzing CIA Factbook with SQL/Pandas
Analyzing Star Wars Survey Data
Analyzing High Schools in New York City
Visualizing The Gender Gap In College Degrees
Visualizing Earnings Based On College Majors
Analyzing Thanksgiving Dinner
Exploring Gun Deaths in the US
Exploring U.S. Births
