Rental Bike Share Prediction Mini Project
Rental Bike Share from vehicle data
@kaggle.swatikhedekar_rental_bike_share
Rental Bike Share from vehicle data
@kaggle.swatikhedekar_rental_bike_share
Context:
Bike sharing systems are new generation of traditional bike rentals where whole process from membership, rental and return back has become automatic. Through these systems, user is able to easily rent a bike from a particular position and return back at another position. Currently, there are about over 500 bike-sharing programs around the world which is composed of over 500 thousands bicycles. Today, there exists great interest in these systems due to their important role in traffic, environmental and health issues. Apart from interesting real world applications of bike sharing systems, the characteristics of data being generated by these systems make them attractive for the research.
Content:
The Dataset you can get through this link: Dataset
Predict the total count of bikes rented during each hour.
CREATE TABLE hour (
"instant" BIGINT,
"dteday" TIMESTAMP,
"season" BIGINT,
"yr" BIGINT,
"mnth" BIGINT,
"hr" BIGINT,
"holiday" BIGINT,
"weekday" BIGINT,
"workingday" BIGINT,
"weathersit" BIGINT,
"temp" DOUBLE,
"atemp" DOUBLE,
"hum" DOUBLE,
"windspeed" DOUBLE,
"casual" BIGINT,
"registered" BIGINT,
"cnt" BIGINT
);Anyone who has the link will be able to view this.