Manjunatha Veerappa

Collected, analyzed and interpreted huge amount of RecceMan data. Achieved an accuracy of 92% using Random Forest algorithm, which is an increase of 12% than the previous model. Individually handled a project (explanation system of the model), which made customer rely on the model and its prediction. Successfully deployed the entire project to the production internally via tmux and externally via Kubernetes.

Explored different interpretable methods to explain the reason behind the prediction of a Residual Neural Network model. Integrated all the explainable methods along with the dashboard for data visualization, which made the model's internal mechanism transparent.

Acquiring data from different sources, maintained and managed an institute’s PostgreSQL database. Interpreted the data, analyzed the results using statistical techniques and provided ongoing reports.

Performed data analysis of the US based insurance data. Responsible for managing and maintenance of Oracle DB. Performed programming duties in the development, implementation and support of information systems.

Computer Science and Advanced Programming emphasized on Python & C++. Pattern recognition concepts with insights into image recognition and real-time data processing.

Mathematics include statistics, calculus and linear algebra.