A collection of several different python files created with the goal of creating a neural network to make accurate restaurant recommendations.
Download the data from this link and place it into the data folder.
Built on Python version 3.11
A Neural Network trained on the dataset of restaurants. Running the program trains the neural network, then opens a GUI where the user can browse a list of websites to select their favorites. Once they select their favorites, the program will suggest similar restaurants based on the neural network output.
A small script made to show the top 5 and bottom 5 lowest rated restaurant categories.
A script similar to barGraphMaker.py that compares the star ratings and sentiment analysis scores for ratings pertaining to the top 5 and bottom 5 categories.
A small script made to trim the incredibly large Yelp dataset down to a more manageable size.
A visually appealing and responsive GUI to let a user search for restaurants that fit their criteria, potentially to choose a favorite restaurant to be inputted into NN.py.
A script similar to restaurantFilter.py made to trim the large Yelp dataset.
A script used for generating sentiment analysis scores for the reviews using NLTK.
A script that generates a density plot of sentiment analysis scores vs. star rating. Similar to doubleBarGraphMaker.py.