Identify fake news and real news using algorithms like bert,Roberta,Xlnet,Explainable AI with Shap and Nlp techniques on tested data.
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Updated
Oct 25, 2025 - Jupyter Notebook
Identify fake news and real news using algorithms like bert,Roberta,Xlnet,Explainable AI with Shap and Nlp techniques on tested data.
A hybrid machine learning model as a combination of natural language processing and time series forecasting for stock market prediction using two different types of datasets: numerical and textual data.
Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.
This project builds a deep-learning-based heartbeat sound classification system using MFCC features and multiple models including CNN, BiLSTM, and a Hybrid CNN–BiLSTM architecture. The system detects and classifies heart sounds into normal, murmur, and artifact categories, supporting early cardiac abnormality detection.
Publication Title - Novel Cyber Attack Detection Using Hybrid Deep Learning Model. Published on - International Journal of Science and Innovative Engineering & Technology (IJSIET) Vol.1, Sep 2022
This project implements a hybrid deep learning model capable of recognizing emotions in human speech by analyzing acoustic characteristics of audio signals. Manual classification of emotions in voice recordings is time-consuming, inconsistent, and lacks scalability. This system automates this process by detecting emotions .
Interactive simulation platform for thyroid nodule classification using ML, DL, and hybrid models. Built for education, visualization, and model evaluation on real ultrasound datasets.
BullBearAI: Stock market prediction built for clarity. Uses a hybrid LSTM-CNN model to deliver actionable insights from complex financial data.
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