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
Design and Implementation of Random Forest algorithm from scratch to execute Pacman strategies and actions in a deterministic, fully observable Pacman Environment.
Analysis of the Restaurant reviews by using the Naive Bayes & the Random Forests Algorithms
This is a Machine Learning model developed with "Decision Trees Algorithm" and "Random Forest Algorithm" to predict the turnover of HDFC bank with a given dataset of the previous turnovers and features.
Men's Outfit Generator and Recommendation using Random Forest Algorithm. Hue-Fit app AI API services.
Instagram Fake account detection ML model using SciKit Learn
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