Turning data into knowledge, One step at a time
This past summer, I had the chance to take part in the Summer Undergraduate Research Experience (SURE) at Lewis University, and honestly, it was one of the coolest things I have ever done as a student. I had done plenty of projects before, like analyzing Pokémon stats, cleaning up UFO sighting reports, or even building... Continue Reading →
Source: https://x.com/Pokemon/status/1106326121228857344/photo/1 This project started with a simple question:"Is there a relationship between a Pokémon’s type and its base stats?" That’s how most data projects begin: with curiosity and a CSV. I loaded the full Pokédex dataset expecting to run some basic distributions: maybe compare average Attack across types, or see if Dragon-types really are... Continue Reading →
When I started digging into the UFO Sightings dataset, I wasn't looking for little green men. I was curious about the patterns hiding behind decades of reports. What people saw, when they saw it, and where they were when it happened. As someone passionate about data storytelling, this project gave me the perfect opportunity to... Continue Reading →
When the semester ended and winter break began, I saw it as the perfect opportunity to focus on skill-building. I spent time diving deep into data manipulation with Pandas and experimenting with machine learning models. It was a challenging yet rewarding experience that left me feeling more confident and equipped for future projects. Here’s what... Continue Reading →
Embarking on the journey of Data Science can be both exciting and overwhelming. There’s so much to learn—statistics, machine learning algorithms, data manipulation, and more. However, a few essential Python libraries can simplify the process and get you up to speed. In this post, I’ll briefly walk you through two fundamental libraries—pandas, NumPy, Scikit-learn, and... Continue Reading →
Learning with Data 