The Fake News Detection Project by MachineMinds (MIT Manipal) identifies and classifies fake news using advanced NLP and machine learning techniques. It preprocesses text data, trains models like Logistic Regression and transformers, and ensures real-time news verification. Developed under Intel
This project focuses on detecting faults in induction motors using machine learning and deep learning models. It preprocesses sensor data, trains models like SVM, kNN, and DNN, evaluates performance, and provides predictions with insights into motor health.
Predicting Solar Power Generation: A Machine Learning Approach using Historical Weather Data and Time-Series Analysis for Accurate Renewable Energy Forecasting.
Analysis of Synchronous Motor Excitation Current using Machine Learning techniques, exploring relationships between Load Current, Power Factor, and Excitation Current
DrugForge is an AI-powered platform designed to revolutionize drug discovery by leveraging machine learning models and computational simulations. The platform accelerates the identification of potential drug candidates, predicting key properties and ensuring safety, efficacy, and rapid development.
This Tableau Steam Game Analysis Dashboard offers insights into popular games, trends, player counts, and reviews. It visualizes data such as top genres, revenue growth, regional preferences, peak concurrent players, and user ratings. This helps identify trends and optimize gaming strategies.
Developed a flight price prediction model using RandomForest, Linear Regression, Decision Tree, and more. Integrated Intel oneAPI with oneDAL's library for faster computation. Evaluated models using R², MAE, MSE, and RMSE. Saved the optimized Bagging Regressor for future use.