I developed ReviewGuard, an NLP-based system that classifies computer-generated and original reviews using TF-IDF and Logistic Regression. It achieved 93.16% accuracy on a held-out test set, with 94.88% precision and 91.24% recall for computer-generated reviews.
ReviewGuard supports individual predictions and batch CSV analysis. I evaluated it using precision, recall, F1-score, and a confusion matrix.
For my Titanic Survival Prediction project, I trained a Logistic Regression model using Pandas, NumPy, and Scikit-learn. I also practice data cleaning, preprocessing, and exploratory data analysis.
I’m studying Computer Science and Engineering (AI/ML) at K.R. Mangalam University after completing a Diploma in Mechanical Engineering at Madhupur Polytechnic College. I’ve solved 201 LeetCode problems and completed hands-on robotic systems training with sensors, motors, actuators, and microcontrollers.
