• Developed multiple predictive models with 90% accuracy for forecasting the daily-hourly bike rental count using Python & Machine Learning techniques like Regression, Clustering, Ensemble, Neural Network to achieve maximum accuracy • Conducted end-to-end analysis that included data gathering & requirement specifications, exploratory data analysis using Tableau • Discussed impact of accurate & efficient demand forecast in vehicle rental space in terms of cost saving & better customer service
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Developed multiple predictive models with 90% accuracy for forecasting the daily-hourly bike rental count using Python & Machine Learning techniques like Regression, Clustering, Ensemble, Neural Network to achieve maximum accuracy
Aniket-Thopte/Demand-Forecasting-Public-Bike-Rental-Predictive-Modeling-
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Developed multiple predictive models with 90% accuracy for forecasting the daily-hourly bike rental count using Python & Machine Learning techniques like Regression, Clustering, Ensemble, Neural Network to achieve maximum accuracy
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