My First Machine Learning Project: Sentiment Analysis with Hugging Face As a recent graduate from the University of Maryland Global Campus with a BS in Software Development & Security, I wanted to dive into practical machine learning applications. I decided to create a sentiment analysis model using Hugging Face's transformers library - a perfect blend of my interests in AI and software development. What I Built I developed a sentiment analysis model that can determine whether a piece of text expresses positive or negative sentiment. The model is built on top of DistilBERT (a lighter, faster version of BERT) and trained on the IMDB movie reviews dataset. What's cool is that anyone can now use my model through the Hugging Face Hub! Technical Details Base Model: I used distilbert-base-uncased as my starting point Dataset: Trained on IMDB reviews (1000 training samples, 200 test samples) Metrics: The model tracks accuracy, F1 score, precision, and recall

Project Plan for Restaurant Reservation System Prepared By: Michael Bennett and Team 3 Team Members: Nalani Arita: Project Manager (PM) Madilyn Jones: Test Director (TD) Aaron Mitchell: Software Designer (SD) Daniel Keenan: Requirements Manager (RM)/Technical Writer (TE) Michael Bennett: Software Designer (SD)

Subject: Launching Our Restaurant Reservation System Project Message: Hello, Team 3, Michael Bennett here—Mike for short. As we embark on our journey to develop a restaurant reservation system, I’m eager to contribute as a Software Designer alongside each of you. Let's recap our assigned roles and share some exciting updates regarding our project collaboration tools. Team Roles Recap: Nalani Arita: Willingly steps into the Project Manager (PM) role, but open to switching to a Software Designer position if anyone else prefers the PM responsibilities.