Data Science, specifically machine learning forecasting techniques, enables decision makers across a spectrum of industries to set more effective sales targets and plan profitable customer routes that boost top and bottom line growth.
Meeting customer expectations is more difficult than ever, more and more of market share goes to companies who are able to perceive needs rather than react. Whether e-tailing or selling in brick-n-mortar stores, inventory planning is a promising area for predictive analytics,
We examine how professional teams can deploy predictive ticket pricing to capture increased revenue and decrease empty seats.
In post 2 of 4 on biometric modeling, we discuss how sporting teams and goods manufacturers can segment their consumer base using biometric insights.
This is post 1 of a 4-part series focusing how data science can incorporate biometrics for sporting good manufacturers and professional sports teams.
Mosaic writes an in-depth view on the synergies between design thinking & data science. We also examine how these two disciplines can be used together.
Unsupervised learning approaches are very powerful when applied to customer segmentation.
Computer vision is a powerful AI technique with vast business applications. In this white paper, Mosaic examines how to use machine vision for detecting airport layouts from the sky.
This is post #2 of a 2-part series focused on reinforcement learning, an AI deployment approach that is growing in popularity.
In this post I will provide a gentle introduction to reinforcement learning by way of its application to a classic problem: the multi-armed bandit problem.