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fakenewdetection_deployment-over-cloud

The Fake news detection model provides steps to train and deploy the deep learning project over AWS Cloud environment. The code is in python. Execution on AWS Sagemaker and Quicksight. Web application deployed over Flask. Tweets are collected using Nifi

multi-modal---fake-image-detection-using-multiple-modalities

Detecting fake news on microblogging platforms using Text and Image Multi-Modal framework. Used RoBERTa sentence Transformer and EfficientNetB0 for images. The code snippets in Python of the Deep Neural Network employed for the Paper

python-fake-image-using-resnet50-transfer-learning-and-ela

python-regression-solutions-health-insurance-cost-prediction

The Python code for solving a Regression problem for predicting optimum Health Insurance Cost for the Individual. Has through EDA and various Regressor models employed in the prediction. 1. Linear Regression 2. Lasso Regression 3. Elastic Net Regression 4. sklearn.tree.DecisionTreeRegressor 5. sklearn.ensemble.RandomForestRegressor 6. sklearn.neighbors.KNeighborsRegressor

siteforge--deep-neural-network-cnn-

Detecting and localizing forged images on microblogging platforms using deep convolutional neural network. The code snippets in Python using Keras library of the Deep Neural Network employed for the Paper

twitter_india_dataset_ver_03

This dataset have been utilized in research papers. It has Fake and Real images obtained from Twitter. The images are india context specific, meaning fake and real images shared in indian context. The time period is from 2019 - 2021