• 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
