Author: Venugopal Manneni

Hybrid Modeling 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

Objective Understanding impact of viewership on children’s skill levels (tested through an instrument devised by leading child psychologists) after controlling for location, socio-economic levels, gender, pre-exposure levels across a panel of over 5000 children across urban and rural India. Approach

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

Client: A global fast food restaurant chain Objective The client intended to find the performance attributes driving the “Favourite brand” of the category where the population is more heterogeneous. Approach Since the population was heterogeneous in nature, merely aggregating the

Objective The objective was to assess and forecast demand for a retail outlet, using Neural Networks. Approach In order to conduct the analytics, we applied the concept of Multi-Layer Perceptron (MLP) in Neural Networks which can classify and predict the

Objective To understand which product features or applications are most important to a particular market. Approach An online quantitative survey was conducted that included a MaxDiff exercise in which 40 different product features were evaluated on what is best and