Checkout my GitHub

IMDB Movie Review Sentiment Analysis

Skills: Python, Data Visualization(Matplotlib), Machine Learning (Tensorflow, Keras)

Just a small sentiment analysis project.

Image Recognition for Handwritten digits

Skills: R, RMarkdown

Just another small project for recognizing handwritten digits.

Credit Card Approval Predictor

Skills: Python, Data manipulation (Pandas, Numpy), Data Visualization(Matplotlib), Machine Learning (scikit-learn)

It’s common for university students to apply for credit cards, and it’s time for me to get a credit card too! I built a model to try to predict if my credit card would be approved based on data from UCI Machine Learning Repository.

I cleaned and preprocessed the data by scaling and label encoding, imputed missing values with the most frequent values, etc. Next, I fitted the data with logistic regression using sklearn and used grid search to optimize the model. My model was able to predict credit card approval with 87% of accuracy in the end, which is decent.

For fun, I applied my model on my personal data. Yes! My credit card would be approved based on my model predication. When I actually tried to apply for credit card in real life, I indeed received a credit card!

Surviving the Titanic

Skills: Python, Data Visualization(Seaborn), Machine Learning (scikit-learn)

To find the key elements that affect survival on ship wreck, I analysed data from the Titanic ship crash to receive some insights. I first performed exploratory data analysis on the titanic dataset to have a basic understanding of the data. Then, I graphed the importance of features and created beautiful visualizations with Seaborn.

I applied various sklearn algorithms (logistic regression, KNN, decision tree, random forest, SVM) to compare model performance, and found a suitable model with more than 80% of accuracy. To improve my model performance, I performed hyperparameter tuning with GridSearchCV and RandomizedSearchCV. I was able to optimized the model and increased model accuracy to 85% in the end!

Data Science Projects for Bristolgate Capital

Skills: Python (Numpy, Pandas, JIT, Matplotlib, Dash, Streamlit, Flask), SQL (MS SQL Server), Research, Data Verification, Data Analysis, Data Manipulation, Data Visualization

Check out the summary presentation of my four projects at Bristolgate Capital!

Statistics Project for a 3rd Year UWaterloo Course

Skills: R, R Markdown, Research, EDA, Model Selection

This is our third year statistics project for STAT 331, Applied Linear Models. I know, our report is the boring black and white and has a lot of words, but we have to make it academic.

Data Analysis for 180 Degrees Consulting

Skills: Python, Experiment Design, Data Collection, Data Analysis, Presentation, Oral Communication

As an executive of 180 Degrees Consulting, I analyzed and visualized KPIs, collected member feedback and HR data, performed statistical analysis, visualized results and presented them to the rest of the executives team. Here are some of my sample presentations from earlier days: Spring Midterm Member Feedback Review, Winter Midterm Member Feedback Review, Winter KPI EOT Review

Shoe Shop Challenge

Skills: Python, SQL, Data Analysis, Critical Thinking

Applied SQL and Python in real-world cases using data from Shopify. Check out the project.

Statistics and Data Blog Posts

Skills: R, R Markdown, Latex, Data Analysis

Here’s some short data projects and notes that I’ve done using R and R Markdown.

Data Projects

Blog Posts

C++ and Object Oriented Programming

Skills: C++, Git, Presentation, Oral Communication

As the Instructional Support Assistant at the University of Waterloo, I hosted 8 tutorials for 2nd year and 3rd year computer science student. I’ve uploaded them on Youtube after the course ended, check them out!