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All too often companies have only the vaguest idea about what kind of data they’re holding; because such data is very often hidden deeply away in a variety of databases and fragmented across different departments. We identify this data and bring it to light, making it visible, cohesive, comparable and easy to understand so that it really does support YOU in making the right decisions. And if need be, we can also identify any lacking data and define a concept to fill in the gap.
Developing a Recommendation Engine using Hybrid Approach

Developing a Recommendation Engine using Hybrid Approach

Posted by on Aug 22, 2017 in Case Studies | No Comments

  Client: A cloud-based interactive smart video platform that delivers personalized interactive videos on-demand to consumers. Objective Business: Increase time spent on site, number of videos watched, and repeat visits. The Engine: Devise an engine that offers relevant recommendation dynamically and in real-time. The Need Real-time recommendations need to be self-learning and based on massive amounts […]

Classification using higher order interactions: a hybrid approach

Classification using higher order interactions: a hybrid approach

Posted by on Jul 7, 2017 in Case Studies, Insights | No Comments

For representation in this blog, we have considered German credit data for classification of good and bad credit risk using the interaction of the input variables through a hybrid approach. In this approach, first we developed a decision tree for identifying the significant interactions of the input variables and then, a feed forward neural network  […]