Derek Pieser
Automobile Price Estimator and Model Suggester
The purpose of this project was to build a tool that will assist in determining the price of a new automobile and suggest a car model based on its specifications. The data set contains roughly 30,000 records of automotive data that were scraped from The Car Connection website. I used this data to create a regression for the price estimator, and a classification model for the model suggester. Python was used for obtaining data, SQL Server for cleaning, and R was utilized for analysis and model creation.
Kristin Womack
Best Places for Investment Properties in Washington State
As an analyst, my job is to help a customer decide what the best markets are to invest in and maximize chances of success in a house deal. I will research and analyze three aspects to achieve the investment success. The three aspects are mortgage rates trend researching, Net migration pattern researching, house price predicting model/transform model for the best fit. All three aspects are combined and making successful house investment.
Heidi Leonard
Book Recommender Using Collaborative Filtering
Create a recommender system for a brick-and-mortar bookstore that improves customer engagement and increases revenues by making the service and selection desirable; and provides customers with a personalized experience that big-box stores and online retailers cannot match.
Kirby Chen and Tony Tate
Helping the Mariners Win a World Series
We use PCA analysis to better understand the strengths and weaknesses of teams around the league. We can use this information to tailor our game plan to our opponent and get an edge in the game. We use logistic regression to identify potential hall of fame players. There is a link between regular season wins, post season wins and number of hall of famers on a team.
Hieu Nguyen and Anh Phan
House Market Insider
This project is about predicting the housing’s prices market for new investors who have limited cash in hand and want to start investing. We used couple-analysis method in order to give our target audience a general picture about the market.
Donald Mains
Predicting Electric Demand
Predicts electrical demand of Puget Sound Energy using a variety of forecasting techniques including simple moving average, exponential smoothing, Muti-Time series analysis and linear regression to better allocate capital, reduce costs and reduce greenhouse emissions.
Amy Hong
Text Analysis on Covid-19 Tweets
Discovering public emotion and sentiment during Covid-19 outbreak by using text analysis on twitter texts containing keywords as covid19 and coronavirus
Jaan Veanes and Nick Waine
Wine Quality Predictive Model
Our project is focused on the process of building a model intended for use by winemakers. The goal of the model is to predict the quality score (1-10) of a sample of wine based on historical chemical component and quality score data. After testing a sample of wines for levels of acidity, chlorides, sulfates, as well as other components, winemakers would be able to input the data into the model to obtain quality score prediction. Using this knowledge, wine producers would be able to see what adjustments they need to make in their production processes to gain better ratings, increased brand reputation, and more sales.
Last Updated February 29, 2024