My Projects

Showcasing my data science projects for potential employers to view.

A laptop displaying a LinkedIn profile page is placed on a light-colored surface. To the left of the laptop, there is a white candle in a glass holder and a green plant in a white textured pot.
A laptop displaying a LinkedIn profile page is placed on a light-colored surface. To the left of the laptop, there is a white candle in a glass holder and a green plant in a white textured pot.

SEO Analyzer 2024

An interactive Streamlit app for analyzing and optimizing website SEO. This tool evaluates critical SEO factors like keyword usage, meta tags, headings, and image alt attributes, while identifying areas for improvement. Features include keyword extraction, bigram frequency analysis, and a user feedback tab. Perfect for enhancing site visibility, user experience, and search engine rankings. Working with libraries such as pandas, numpy, beautifulsoap to build the backend than utilizing streamlit as the front end for better UX

Data Analysis of PEH

Developed data visualizations to communicate insights effectively to the Partners Ending Homelessness organization in Monroe County, NY. Its the Primary planning and coordinating body for homeless housing and services

Realestate EDA

Utilized pandas, numpy, and matplotlib to explore the data further in order to find insights that correlated to real estate hardships for owners and the societal impacts that lead to these findings

  • Objective: Showcasing real-estate investors hardships when it comes to maintaining the quality of properties

  • Approach: Utilized pandas, numpys and matplotlib for data exploration, preprocessing and visualization

  • Results: explore presentation above for results

  • Visuals: explore presentation above for visuals

  • Objective: PEH had mass amounts data that was being stored and never being analyzed, that was an issue for the growth of the Non-profit, Unstructured and unorganized data hinders a growth for any business that is looking to improve efficiency

  • Approach: Utilized pandas, numpys and matplotlib for data exploration, preprocessing and visualization

  • Results: explore presentation above for results

  • Visuals: explore presentation above for results

  • Objective: PEH had mass amounts data that was being stored and never being analyzed, that was an issue for the growth of the Non-profit, Unstructured and unorganized data hinders a growth for any business that is looking to improve efficiency

  • Approach: Utilized pandas, numpys and matplotlib for data exploration, preprocessing and visualization

  • Results: explore presentation above for results

  • Visuals: explore presentation above for results

Movie Recommender System Chatbot

Collected data from rotten tomatoes, cleaned and preprocessed that data to be most efficient in creating a chat bot that is able to recommend movies for specific users such as adults and teens.

Real vs. Fake Job posting Topic Modeling

Showcased the difficulties b/w differentiating fake from real jobs. Emphasized the best practices to combat this to increase employer responses to one's application

a man holds his head while sitting on a sofa
a man holds his head while sitting on a sofa
Healthcare Employee Attrition

This Project focuses on healthcare employee attrition analyzing the key factors that lead to this, and the answer may correlate with other industries as well. I worked with the random forest model to showcase my findings after cleaning and preprocessing the dataset to ensure its readiness

Spotify Data Analysis in Tableau

Objective:
Analyze and compare the popularity of Jay-Z and Nas using key metrics like album sales, song counts, and speechiness to explore the impact of their historic rivalry

Approach:
Used Tableau for data visualization and analysis. Data was sourced from CSV files containing metrics on albums, songs, streaming stats, and lyrical attributes.

Result:
Jay-Z demonstrated stronger commercial success, while Nas retained significant cultural influence. The project showcases how Tableau can effectively highlight trends and insights in music data.