I'm Janzen Liu, a Neuroscience graduate from the University of Toronto that has found a passion for identifying solutions in data driven problems and their applications to real world scenarios. I'm currently residing in Toronto and acitvely looking for opportunities in the field.

I have found many interests and hobbies that I have been privilidged with to explore, all thanks to my parents. Piano 🎹, dance 🕺🏽, Taekwondo 🥋, and gaming 🎮 have all been things I am passionate about and have been a real life saver during the long long months of COVID. Feel free to contact me at my email.

• Used job posting data provided from Kaggle to determine job posting legitimacy based on various criteria
• Performed exploratory data analysis on parameters within the data set and visualized data using Matplotlib and NLTK
• Assisted and regularly communicated in a team environment to ensure steady workflow to meet deadlines
• Achieved a ML model that could predict fraudulent jobs with an accuracy, precision and recall rating of > 98%

• Performed credit risk analysis using artificial intelligence by applying various supervised machine learning models such as the ones found in SMOTE, sklearn, and imblearn libraries
• Applied under-sampling, over-sampling and combination sampling to compare performance of sampling models
• Calculated balanced accuracy scores and confusion matrixes to summarize the data post analysis

• Analyzed product reviews from the “Video Games” department of Amazon to determine biases behind product reviews
• Used PySpark to perform ETL on datasets acquired from Amazon’s databases and then exported the data into a pgAdmin server with appropriate data frames and tables
• Filtered the data to meet certain criteria in determining the legitimacy of reviews and provided a written overview of the project

Math is a difficult subject but has gotten a bad rep as teaching methods have been limited due to technology. However, advancements and users such as 3B1B along with its great community has developed a beautiful library for math visualizations. In an effort to better improve math delivery in our education system, this on going project aims to cover vital math topics in a visually appealing manner and will be provided free to educators. (WIP, Learning)