In the recent years transportation has seen a tremendous growth. The technology has improved so fast that the people can gather all the information and check for the arrival and departure of the bus, train just by using the app. Now a day, Bike sharing system is gaining more and more popularity as people are tending to use public transportation because of low cost and low maintenance and easy to use. Bike sharing system is one such service provided for the people which rents bikes to the people for free or with some charges and allows the people to use bikes for some duration from one bike station to another bike station. In this project, the analysis has been made on the bike sharing system in analyzing the number of bikes rented per hour, per day, in weekdays and weekends. And check the day and the peak hours of the people and increase the number of bikes so that it increases the companys business and yields more profit. The implementation of machine learning algorithms has given outstanding prediction models with good efficiency. Here, the popular algorithms like, Linear Regression, XGBoost, SVR, decision tree, Random Forest, PCA have been applied to check the accuracy, sensitivity of each model compare them and suggest the model with high accuracy. ystem has been given from various research work done in this field.