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This is the second project to be completed in Upskill ISA Intelligent Machines. The project was done after the end of the competition. The ensemble of BERT, GPT2, XLNet was used in this model that obtained 0.94656 private scores on Kaggle.
Django application of https://github.com/Tikquuss/eulascript, the Machine learning (ML) solution that review end-user license agreements (EULA) for terms and conditions that are unacceptable to the government
This repository houses three fine-tuned machine learning models for NLP tasks: Text Emotion Recognition, Sentiment Analysis, and Cyberbullying Detection.
We have proposed a multimodal approach. Where we first took the best unimodal for textual and visual data classification by testing and automation process. Then we fusion of the two models which can successfully classify the materials that have been damaged using the image and text data. EfficientNetB3+BERT multimodal better accuracy with 94.18%