AutoForm SP vs Cluster2A

AutoForm™ a cloud-based mobile data collection app for the iPad and iPhone offered by Stantec for our clients and partners. Powerful custom forms are created quickly by our staff for each client project and available for download with AutoForm™. Existing enterprise data can be taken offline for onsite review and correction. New and modified field data is “synced” securely to a Stantec hosted mTOOLS™ collaborative website for analysis and reporting with your team and clients. Using AutoForm™, you can: • Collect data efficiently with intuitive touch interface • Improve data quality with field access to existing data, images and maps • Gather robust data including GPS, Photos with mark-up and signatures • Sync to cloud for instant visibility for office and field collaboration • Reduce mobilization time with library of existing form templates • Configure new forms quickly and easily with flexible platform • Maintain key relationships with flat or hierarchical data • Streamline data flow from the field to the client Combine AutoForm™ with other mTOOLS™ products to provide rapidly deployed enterprise solutions for field capture, analysis and reporting. Stantec is a strategic consulting, technical engineering, environmental and construction services firm leading the wet infrastructure sector. We partner with our clients in Building a Better World, providing a full range of services for projects and programs that focus on water, energy and environmental services. To know more about AutoForm™ and mTOOLS™ contact us via email at ptechsupport@stantec.com mTOOLS™ - Making Data Easy

Machine learning has become a powerful tool, revolutionizing how industries operate. Unsupervised learning is a machine learning method that analyzes and discovers hidden patterns, structures, or relationships in unclassified or unlabeled data. It is widely used to improve customer experience, provide personalized recommendations, optimize operations, and drive innovation. K-means and DBSCAN are two commonly used unsupervised learning algorithms. Common application scenarios: Customer and market segmentation: Grouping customers based on their behavior, demographic characteristics, or purchase history for targeted marketing and personalized recommendations. Retail analytics: Identifying "hotspot areas" in a store through cluster analysis of customer locations. Cluster2A combines two machine learning algorithms, K-means and DBSCAN, to help users with small datasets take their first steps into the world of machine learning more easily and enjoyably.