Chloe Ho - Portfolio

Portfolio

View my works below to see my analysis and visualizations

This portfolio demonstrates my ability to extract meaningful insights from complex datasets and build data models to solve real-world problems.

Exploratory Analysis & Sentiment Analysis

Analysis of Top 10 Data Science Channels using Youtube API

This is a data-driven project aimed at exploring key factors that influence the success of YouTube videos in the data science niche. The project involves leveraging the YouTube API to obtain video data, conducting in-depth analyses, and dispelling common myths surrounding video performance. By utilizing various data analysis techniques, NLP, and Sentiment Analysis, I aim to provide valuable insights to content creators, data science students, and enthusiasts.

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Exploratory Analysis & Machine Learning

Airbnb in NYC Price Prediction

This end-to-end project focuses on analyzing Airbnb pricing in New York City in 2019 using Tableau, and employs seven models to predict Airbnb listing prices. The models used include Linear Regression, Decision Trees, Random Forests, Boosting, and Support Vector Machine. The performance of each model was evaluated on test data, and the results indicate that the Support Vector Machine model is the most reliable model for Airbnb prices.

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Web Scraping

Job Market Analysis: Web Scraping indeed.com

This project involves using Python and Selenium to scrape job postings from Indeed.com and perform data analysis to extract insights about the job market for software engineers in three key locations: Seattle, San Francisco, and New York City. The objective is to identify the companies that are hiring the most, determine the distribution of job titles, and analyze the frequency of certain keywords in job descriptions to determine the most in-demand skills and qualifications.

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Exploratory Analysis & Regression

MBA Post-score and Performance Prediction

This project performs an exploratory analysis of demographics among MBA applicants, such as age, gender, and education. It utilizes k-means clustering, linear regression, and logistic regression to predict the post-score of MBA applicants and assess the probability of their achieving successful MBA performance. Through these methods, the project provides valuable insights into the factors influencing MBA outcomes and offers predictive models for evaluating future performance.

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Tableau Visualization

COVIDStats: Visualizing COVID Infection Rates

This project uses SQL queries to extract COVID data, separates it into deaths and vaccinations datasets, and creates an interactive Tableau dashboard. The dashboard displays graphs on Global Statistics, Total Deaths per Continent, Percent Population Infected per Country, and Projected Percent Population Infected. Its aim is to provide insightful visualizations for analyzing COVID deaths and infection rates.

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