Guess_who User

Developed data pipelines for classifying Gravitational Wave signals using neural networks and advanced unsupervised learning techniques, increasing data processing efficiency by 25%. Implemented time-series analysis to enhance detection rates by 20%.

Analyzed IT and financial data from databases, processing datasets of over 0.5 million rows using SQL, Python, and Power BI. Improved anomaly detection accuracy by 20% and created interactive dashboards to streamline compliance monitoring, reducing reporting time by 30%.

Designed and deployed an object detection model using YOLOv8 and OpenCV, achieving 90% accuracy in real-time video privacy applications. Built a custom GUI application to reduce processing time by 40%.

Created an ML model using Random Forest Classifier to predict machine failures, achieving 94% accuracy. Implemented an interactive dashboard for predictive insights, boosting user engagement by 40%.

Developed a complaint classification model using Naive Bayes and SVM, achieving 88% and 79% accuracy respectively. Built text processing pipelines to analyze over 10,000 customer complaints.

Led AI/ML workshops for over 70 members, increasing participation by 90%. Organized events to boost awareness of AI/ML technologies, achieving a 50% rise in member engagement.

Grade: CGPA - 9.23

Pursuing a B.Tech in Artificial Intelligence and Data Science with a CGPA of 9.23. Relevant coursework includes Data Analysis, Statistical Modeling, Data Visualization, Gen AI, Machine Learning, Predictive Analytics, Probability and Statistics, and Natural Language Processing.