Evaluated several factors to determine the risk of diabetes in patients, based on a survey of 70,000+ participants
Performed quantitative analysis on a survey of 15,000 employees to determine the key factors responsible for employee attrition, implemented several machine learning models to predict the same
Conducted comprehensive quantitative and statistics analysis, including in-depth exploratory data analysis and data visualization in R, to examine cervical cancer risk factors, uncovering correlations among 12 predictors
Designed a conceptual and relational database model for an online thrift store, Garage Sale. Created a python pipeline to access the database created in MySQL and perform analytics
Devised an efficient security system by building a pipeline that detects numberplates and identifies the registered owners, implementing ai models like YOLO V4 and PyTesseract for real-time detection of numberplates
Developed a solution using Anomaly Detector to identify unusual behavior in public in real-time using Convoluted Neural Networks (CNN) model Autoencoders and fine tuning it to achieve an accuracy of 72%
Harsh Mahajan
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