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Software Engineer
CODESOFT•  December 2023 - Present
Developed and implemented a robust machine learning model to detect fraudulent credit card transactions, utilizing logistic regression algorithm and a dataset of credit card transaction information. Achieved an accuracy rate of 95% in classifying transactions as fraudulent or legitimate. Implemented a predictive model to forecast customer churn for a subscription-based service, utilizing historical customer data and algorithms such as random forests. Achieved an accuracy rate of 80% in predicting customer churn, enabling proactive retention strategies to be implemented. Created an AI model using TF-IDF techniques with Naive Bayes classifier to accurately classify SMS messages as either spam or legitimate. Achieved a precision rate of 92% in identifying spam messages, significantly reducing the risk of users being targeted by spam campaigns.
Python developer
INTERNPE•  July 2023 - August 2023
Applied code optimizations that improved the efficiency of existing software by 30%, leading to faster data retrieval and increased productivity. Developed and tested Python scripts to automate data analysis procedures, resulting in a 50% reduction in manual data processing time.
Education
COE, Roorkee (College of Engineering)
Electrical Engineering, B.Tech•  August 2014 - August 2018
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