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How to leverage machine learning for commuter forecasting?
The transit agencies’ foremost responsibility is to ensure passengers’ safety and on-time transit. Employing state-of-the-art machine learning techniques in transportation can help governments and organizations smoothly plan, manage, and implement their services.
The transportation agency is better positioned to forecast transit demand and manage its services accurately through mining departmental data and extracting hidden insights. Building next-generation solutions solve widespread transit challenges while establishing more sustainable systems.
Use case highlights:
- An in-depth analysis of a transit system in the San Francisco Bay Area
- Reveals insights on parameters like the busiest time of the day, the busiest day in a week, the count of passengers traveling during the night, etc.
- Machine Learning models leveraged to forecast average weekday commuter traffic
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Broad-spectrum of products and services employing leading-edge technology, providing a strategic and competitive advantage
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Unmatched standards for quality, scalability, and performance create exceptional value, propelling organizations to the next level of insight and action
End-to-end services from consulting to full-cycle software development
Empower non-experts to use machine learning models and techniques without the need for prior expertise in the field
Complete adherence to data and security regulations such as HIPAA, Data protection 2018, etc.