Hello, I am Junhyuk Lee. Many of you may know me as Joseph.
I graduated from the University of California, San Diego (UCSD) with a major in Applied Mathematics.
I'm a curious and passionate learner with a wide range of interests.
My interests primarily lie in data science & statistics, machine learning,
cryptography & cybersecurity, and applying math to solve real-world problems.
Beyond academics, I enjoy a variety of creative and active pursuits.
I enjoy reading, writing stories, drawing, playing video games, and listening to music.
I like to workout, play badminton, and read philosophy.
I also regularly write in my blog, which you can find here.
I'm always looking forward to learn and grow.
Feel free to connect with me!
This is my personal blog, where I share my
thoughts, experiences, and knowledge on various topics,
including data science & statistics, programming, mathematics, and more.
I also share my personal experiences and insights on learning, productivity, and self-improvement.
Click the button below to see all of my past blogs:
Git, GitHub, Jupyter Notebook, Matplotlib, NumPy, Pandas, Python, Seaborn, Scikit-learn
This is my final project for Data Science in Practice.
I collaborated with a cross-functional team to analyze the relationship between an applicant's credit background and their loan approval status.
We cleaned the data for missing entries, performed Exploratory Data Analysis (EDA), utilized data visualizations, and constructed a model.
API, CSS, HTML, Git, GitHub, JavaScript, Jupyter Notebook, NumPy, Pandas, Python, Requests, Scikit-learn
This is a data science project that uses the public Pokemon RESTful API.
I used the Python requests library to retrieve data from the API,
and use it to create the dataset, clean the data, perform EDA, visualize the data,
answer a few data analysis questions, and build machine learning models.
Git, GitHub, Julia, Jupyter Notebook
This lecture on K-Means Clustering was my final project for MATH 157 at UC San Diego.
In this lecture, I covered the theory and implementation of K-Means Clustering in Julia,
as well as real-world applications such as image compression.