This project is about anomaly detection in social network, completely on network structure. We use random forest algorithm to train and test our classifier. Also, we are going to see how the effect of increase of trees in forest to the accuracy of prediction.
It is a ML based model to detect fake URLs and QR codes, using adv. data cleaning to improve accuracy. Built a Flask-based RESTful API for real-time fraud checks, allowing easy use in web and web apps. Designed a responsive JS front end to connect with the backend, showing fraud risk scores, confidence levels, and key risk factors for users
Analysis of the Restaurant reviews by using the Naive Bayes & the Random Forests Algorithms
Design and Implementation of Random Forest algorithm from scratch to execute Pacman strategies and actions in a deterministic, fully observable Pacman Environment.
Apprenticeship project with Indian Institute of Science. Objectives were to Model tumor and immune cell interaction in the presence of MMP & TIMP by varying their diffusion rates and check the effect of MMP8 on these interactions. These simulations provides insights into how ECM remodelling shapes cancer progression.
Outfit Generator and Recommendation API
Instagram Fake account detection ML model using SciKit Learn
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