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)