I collaborated with my groupmates, Cayden, Eric, and Jason to make our project. Our project looks at the Sepal Length, Sepal Width, Petal Length, Petal Width, and determines what type of flower the user is describing. It then will show a picture of that flower in response. Our machine learning model takes a csv data set of a ton of flowers, looks at their sepal and petal sizes, and comes up with the closest flower.
using our own data set
developing frontend to backend api
applying to a team project
adding as supplemental feature to your CPT
frontend with purpose, ie “do you …” similar to titanic idea
Instead of the titanic, our team decided to create an iris predictor. The main functionality for this code was to receive information from the user about the type of flower they are trying to identify, and help them identify it using the physical traits of the flower. Like the titanic, this takes information about the flower, and applies it to a machine learning backend which returns the name of the flower.