Brittanie Morgan

Description:Using machine learning, I highlighted similar symptons among heart disease patients and predict the patients who are likely to have heart disease. Data was pre-processed by removing missing values, removing irrelevant columns and encoding categorical variables. I conducted exploratory analysis and hypothesis testing to find and validate any relationship between variables. The Support Vector Machine model used had an accuracy of 84.8%.

Description:Using natural language processing, I developed a machine learning model that analyzes email content to determine whether it is spam. The data preprocessing involved normalizing the text by converting it to lowercase, removing punctuation and stop words, and applying lemmatization, followed by vectorization using TF-IDF Vectorizer. The model was Support Vector Classifier (SVC) with an accuracy of 97%.

Description: Developed content-based product recommendation system for fashion retail products that given a product will return the 10 ten most similar products. Utilized cosine similarity matrix to rank similarities between products based on features such as colour, product type and description.

Description:I created a destop application that allows a small fashion retail business to automate common business fucntions.It features point of sale functionalities, inventory management, promotions, customer relationship management, report generation, user management, and authentication.

Description: Developing a web application that will allow users to create, view and register for events. It will also send email reminders and suggestions for events. Event attendees will be able to place reviews and event creators will be able to view graphical summaries of the reviews.

Description: Created a dynamic website that allows customers to place orders based on the menu provided by the restaurant. It allows authorized personnel to modify the menu, monitor pending orders and deliveries, and automates graphical reports to access the performace of the restaurant.

My role: I implemented the features to place an order and monitor pending orders and deliveries.