ndpereyra.github.io
Hello, and welcome to my website. As stated above, due to my University’s policy surrounding acacdemic integrity, I can’t post my code to a public repository, but I can link pages where I describe these projects in greater detail.
This was one of the projects that I was assigned in my iOS app development course. It was the culmination of three separate projects designed to introduce us to programming in Swift, creating basic user interfaces and connecting the backend model with the frontend view, and finally adding animations and making the user interface more complex and user friendly.
The app is similar to games like 2048 and the like. A 4x4 grid is displayed, with a few of the spaces filled up by numbers. Users have to match like numbers to create a larger number (ie combine 3 and 3 to get 6), with the ultimate goal being to get as high a score as possible.
This project taught me a lot about programming in the Swift language, from the basics, to advanced topics like connecting models and views, adding animations, positioning objects on the screen, saving information when the application is closed, and more.
Analyzing the New York Stock Exchange
This project was a group one, and served as the final for my Introduciton to Data Science course that I took in the Fall 2021 semester. Our professor had tasked us with finding data on the Internet, and then going through the “Data Science pipeline” by scrapping the data source, operating upon the data to be able to use it, performing initial analysis, creating visualizations, then finally machine learning.
My group found several documents containing data on the New York Stock Exchange from 2012 to 2016, and decided to use this as our project. The entire project can be found on the link above, along with our code and analysis. In short, however, we created visualizations plotting several companies and their performance over time, along with industries as a whole, in order to determine which companies did better, and which will coninue to perform well if all holds.
Following that, we performed linear regression on different types of data pertaining to a company’s fundamentals and their yearly statements. Our thought process was to use linear regression to narrow down the many variables a company releases each year, such as Cash Ratio, Total Revenue, Total Liabilities, etc, in order to determine which are the most important, and affects a company’s performance the most. The results can be found in the project above. After that, we created a neural network to try and test our findings, to see how well the model performed.
Tools used in this project include: Python, Jupyter Notebooks (through Google Colab), Pandas, NumPy, SciKit Learn, MatPlotLib, TensorFlow, and other Python libraries
This was an optional extra credit project assigned by my professor. The link contains the ReadMe from my professor that fully describes the project, but in summary, I was instructed to create a working version of TikTok, where users could view videos uploaded to a Firebase database, upload videos, as well as like the videos they viewed. I also had to sort the videos in the database by the number of likes the current user has given, as well as the number of times a video was viewed.
This project futhered my understanding of the Swift programming language, as well as helped me learn much about using Firebase with Swift, such as how to connect to the database from the app, and how to parse through the database snapshot to obtain useful information, like the video URL to use with the video player.