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JerryZhaoYJ/README.md

Hi, I'm Jerry Zhao

I am an MS in Applied Data Science student at the University of Chicago, with interests in machine learning, business analytics, finance, consulting, and data-driven decision-making.

About Me

  • MS Applied Data Science @ University of Chicago
  • Background in mathematical statistics and finance
  • Experience across finance, consulting, telecommunications, and business analytics
  • Interested in applying Python, SQL, machine learning, and visualization to real-world business problems

Technical Skills

Languages: Python, R, SQL, Java

Machine Learning: classification, logistic regression, linear SVM, Naive Bayes, KNN, decision trees, random forests, clustering, model evaluation, error analysis

NLP & Text Analytics: tokenization, stop-word removal, TF-IDF, LDA topic modeling, word-frequency analysis, sentiment features, text classification, authorship analysis, document classification

Data & Databases: pandas, NumPy, tidyverse, MySQL, Azure SQL Database, IBM Db2, Amazon RDS

Visualization & BI: matplotlib, ggplot2, Power BI, Tableau, Amazon QuickSight, Excel VBA

Workflow: Jupyter Notebook, R Markdown, GitHub, reproducible project structure, README documentation

Featured Projects

Research Article Subject Tagging

Multi-class NLP project for automatically tagging research articles by subject using title and abstract text.

Spotify Song Clustering Recommender

Large-scale unsupervised learning project using Spotify audio features and lyrics to discover latent song clusters and support content-based recommendation.

Essay Topic Modeling & Authorship Detection

R-based text analytics project using LDA topic modeling, pairwise word correlations, and logistic regression to explore essay prompts and AI-versus-human authorship patterns.

E-Commerce Recommendation Engine Modeling

Customer analytics project comparing logistic regression, KNN, decision trees, bagging, and random forests for e-commerce recommendation decisions.

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  1. spotify-gengre-clustering-song-recommender spotify-gengre-clustering-song-recommender Public

    Large-scale music discovery project that clusters Spotify tracks using audio features and lyrics, compares MiniBatchKMeans, DBSCAN, and hierarchical clustering, and demonstrates content-based recom…

    Python

  2. ecommerce-recommendation-engine-modeling ecommerce-recommendation-engine-modeling Public

    R-based machine learning project comparing logistic regression, KNN, decision trees, bagged forests, and random forests for an e-commerce recommendation decision task.

    R

  3. essay-AI-authorship-detection essay-AI-authorship-detection Public

    R-based text analytics project that uses LDA topic modeling, pairwise word correlations, and logistic regression to recover hidden essay prompts and explore AI-versus-human authorship patterns.

    HTML

  4. research-article-subject-tagging research-article-subject-tagging Public

    Multi-class NLP pipeline for tagging research articles by subject using title and abstract text, with TF-IDF features, non-deep-learning baselines, and detailed error analysis.

    HTML