Synopsis: Around 5 years of experience in executing data-driven solutions to increase efficiency, accuracy, and utility of internal data processing. Experienced at creating classification, regression and clustering models using predictive data modeling. NLP problems like Sentiment analysis and Topic Segregation deliver insights and implement action-oriented solutions to complex business problems.
PROJECT DETAILS:
Building of the model which take input the test cases executed by the Test management Tool and find the clusters in the test cases and rerun those test cases where it would reduce the human effort of running the failed test cases.
Roles & Responsibilities:
· Extraction of the Data from test management tool for the model building.
· Applying the pre-processing steps with data(Nominal, Ordinal) which interns produces the clean data which would be useful for the model building
· Transforming the Consumed the data into the features for providing the input to the model with the useful techniques
· Building the clustering model choosing the appropriate algorithm (Model) based on the multiple hyper-parameters.
· Automating the clustering mechanism where the incoming data will be feed in to the model and it can be retrained on the new data and create new clusters.(Continuous Learning)
· Deploying the model in the client environment that would help to testers the effort of rerunning the failed test cases.
Operating Systems : Windows, Linux
Participations:
1. I’m with the team of 4 people were finalists for the TechGig competition sponsored by Global logic and insurity for the idea of building the image classification model using Neural Networks for issuing the insurance of the damaged vehicle.
2. I have participated in the Mutilabel classification (NLP) competition powered by TechGig.