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Sherry You's Data Science Portfolio

Introduction

Hi, welcome to my portfolio! My name is Sherry You and I am currently a Masters of Management Analytics Candidate at the University of Toronto, Rotman School of Management. I recently graduated from the University of Toronto with a Bachelor's of Commerce, specializing in management with focuses on finance and data science.

In this repository, you can find the various data science-related projects I completed during the third and fourth years of my undergraduate studies and some projects I completed for the Analytics Colloquia in my graduate program. I have separated my projects into the following folders based on the course that I have taken:

Graduate Course Project

  1. Garbage Classification using the Vision Transformer (ViT) (RSM8521 Leveraging AI and Deep Learning Tools in Marketing)
  2. Optimizing Supply Chain Management (RSM8423) - BioPharma Case Study

Graduate Colloquia Projects

  1. Social Network Analysis (RSM8431 Analytics Colloquia) - Project
  2. Python ArcGIS (RSM8431 Analytics Colloquia) - Project
  3. Cloud Computing (RSM8431 Analytics Colloquia) - Assignment
  4. APIs (RSM8431 Analytics Colloquia) - Assignment

Undergraduate Course Projects

  1. Machine Learning and Data Mining (ECO480) - Research Project
  2. Management Analytics for Service and Healthcare Management (RSM412) - Projects
  3. Machine Learning in Finance (RSM338) - Projects

Interest Projects

  1. SNA and GNNs
  • This folder contains the code and material for an interest project, "Identifying Illegal Wildlife Trafficking Networks using Social Network Analysis and Graph Neural Networks"
  • Constructed graphs, implemented Leiden algorithm for community detection and built a heterogeneous graph neural network (HGNN) to detect illegal wildlife trafficking networks. Currently fine-tuning the HGNN and testing different convolutional layers such as EGATConv and GINEConv.

Python Libraries and Modules

Through my courses, we used various Python libraries and modules including:

  • NumPy
  • Pandas
  • Matplotlib
  • Sklearn
  • Seaborn
  • Ciw
  • PuLP
  • Scipy
  • Beautiful Soup
  • Geopandas
  • Qeds

Topics and Skills Explored Through My Courses

Through these courses, I had the opportunity to explore various machine learning algorithms including:

  • Linear Regression
  • Logistic Regression
  • K-nearest neighbours
  • K-Means Clustering
  • Decision Trees
  • Random Forests
  • XGBoost
  • Principal Component Analysis
  • Support Vector Machines
  • Neural Networks
  • LSTM networks
  • Deep Neural Network Applications
  • Transformers (BERT, ViT)