ChaitanyaC22/Udacity-AWS-MLE-ND-Project1-Bike-Sharing-Demand-with-AutoGluon
This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.
Predict the number of bikes customers will rent at various times using historical rental patterns and weather data. This helps urban planners and bike-share operators understand and manage fleet distribution. The project takes historical bike rental logs and weather information, then outputs predictions for future bike demand. This is for operations managers or urban planning analysts in cities with bike-sharing programs.
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Use this if you need to accurately forecast bike rental demand without extensive data science expertise, leveraging automated machine learning for speed and efficiency.
Not ideal if you need a deep, granular understanding and control over every step of the machine learning model's internal workings and code.
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Jan 24, 2023
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