Week 4(Final) Blog

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Overall, I am extremely pleased with the work our group has accomplished in such a short time on this project. Despite encountering numerous challenges and sleepless nights, our group still had a positive experience. At the end of the day, regardless of whether our final product works or not, I can assure you that I have learned significantly more in the past few weeks than I have in all my other CS/DS courses at Northeastern. Seriously.

For the final project, my primary contributions included finding and sourcing APIs and websites for data purposes to feed our two machine-learning models. I am responsible for implementing the whole first machine-learning model, a simple linear regression model, from analyzing the dataset in Jupyter to producing the final product on Streamlit. Additionally, I helped in providing code to allow my other group members to upload their datasets into SQL files. Lastly, I helped with any other tasks that were required, especially with Streamlit and the routes as I had taken CS 3200 in the past and had some experience with those features.

The most challenging aspect of this project was collaborating on a “CS” project with a team, particularly regarding the use of Git in a team setting and just learning good CS practices. Prior to the dialogue, my Git knowledge was pretty limited to basic commands such as git push and git pull. However, this project forced my group and I to fully understand how git works if we wanted to avoid any merge conflicts which we definitely didn’t want. Despite these cautions, I encountered some pretty nasty merge conflicts when merging my branch into the main, but at least it compelled me to learn how to resolve these conflicts.

Easily the most enjoyable part of the project was the people. Over the past few days, I grew very close to my classmates as we bonded over the endless challenges of the project. I am constantly amazed by their ability to maintain a positive attitude despite often getting no more than four hours of sleep a night. Their perseverance inspired me to stay positive and push forward, making me a better person. I am incredibly grateful for them and everyone involved in this project. I have no regrets about the past four weeks, and I am so going to miss them back home.

Resume format:

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• Extracted and processed data from APIs and web scraping, followed by creating machine learning models to analyze and predict trends.
• Developed Flask API routes to handle data requests, integrate ML models, and facilitate communication between backend and frontend.
• Built an interactive web application using Streamlit to provide user-friendly access to data insights and predictions.