a airbnb api to provide to front end teams price recommendations based on machine learning for their application based on the city, room type, security deposit, if there is a guest , and what th minimum night one is staying at an airbnb a price is return for the criteria the user decides on.
data.csv
This dataset provides a list of airbnb rentals at all major US cities and the different features and price for them
Flask pickle sklearn pandas numpy tensorflow
/predict' This route is used to predict airbnb price by defining values of each parameter. The model is a CNN model using tensorflow.
`city = string
room_type = string
security_deposit = float
guest_included = int
mininum_nights = int ` To get the price prediction, from the api we need to pass values of parameters in the URL as below
https://airbnbapi-ds.herokuapp.com/predict?city=Boston&room_type=Apartment&security_deposit=200&guests_included=2&mininum_nights=2