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Data Scientist
innodatatics• May 2021 - October 2021
INCIDENT IMPACT PREDICTION: Project aims to analyze the incidents raised by customers and build predictive model that can predict the impact of the incident through different classification techniques with high accuracy. The data is over sampled to its range of values and then it aims to balance class distribution by randomly increasing minority class examples by replicating them. After cleaning the data using proper EDA methods we carried out with further classification techniques, using Decision Tree classification as a feature selection We have gone through different kernels of SVM and KNN which interns gives an accuracy around 94 percent which is slightly lower than Random forest Classifier and Decision Tree. We have used Random Forest classifier in the end.
Education
Steinbeis-Hochschule-Berlin
Data Science, PGD• April 2021 - September 2021
Visvesvaraya Technological University
Mechanical Engineering, BE• August 2014 - August 2021