Teresa Le's Projects
Used AWS, ETL processes and PySpark to work with big data and determine whether reviewers who are a part of Amazon's Vine program (i.e. being paid) are biased and writing more favourable reviews than unpaid reviewers.
Created a Tableau dashboard and story using Citi Bike's data to help provide insights on users and usage
Used Python (scikit-learn) to develop supervised machine learning models to predict credit risk
Used Python and unsupervised machine learning to create a report of cryptocurrencies being traded and classify them using unsupervised machine learning
Automating the production of an election results report
Used Python and Excel to select the top 1000 products to create an aisle for Instabasket shoppers to improve efficiency, customer satisfaction and profits
Analyzed a delivery startup's performance of their new launch in NYC using Excel, SQL and Tableau to propose a strategy for improving their performance
Performing an analysis on Kickstarter data to uncover trends using MS Excel
Used MS Excel to prepare reports and forecasts that are necessary to launch and sell shorts that are part of the May 2022 capsule.
Defined KPIs, created a dashboard and visualized data for executives and SMEs using Power BI to help steer decision-making and track important metrics
Performed statistical analysis using R on the MechaCar prototype production data to gain insights on the production issues for the manufacturing team
Performing web scraping using Python to collect news items about Mars missions
Developed deep learning neural network models using Python (tensorflow, scikit-learn) to predict whether non-profit organizations would be good candidates for donations
Performed an analysis on employees retirements to assist with making decisions regarding hiring strategies using data modeling, SQL (postgreSQL) and pgAdmin
My portfolio guide is a summary of my projects.
Performed an exploratory analysis and visualized rideshare data using Python (pandas, matplotlib) to help improve access to ridesharing services and determine affordability for underserved neighbourhoods
Preparing test data using Python's pandas library so that it can be used for deriving insights about school performance trends and patterns
Used data visualization, association rules learning, and conducted a market basket analysis to uncover trends related to sales and profits to help Superstore make decisions regarding related to their products and pricing strategy.
Used Python, Pandas and SQLite to analyze the weather data and determine whether a surfboards and ice cream business should be opened
Used Javascript to create a filter and allow users to analyze UFO sightings data using multiple different search criteria
Used Python & R to develop ML models to predict sales and derived insights using Tableau and SQL
Used Python, OpenWeatherMap's APIs and Geoapify's APIs to allow users to find accommodations and plan their road trip vacations.