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Deep Learning for Text & Video Sentiment Analysis by asillerpromosyon is a document available to read on EtoBox.

The document presents a project on sentiment analysis that integrates text and video data using deep learning techniques, specifically LSTM networks, Word2Vec embeddings, and CNNs. The developed application achieves an accuracy rate of 85%-90% and aims to enhance the understanding of human emotions for various applications like marketing and research. The project also discusses the implementation of a user-friendly GUI using PyQt5 to display sentiment analysis results effectively.

Author
asillerpromosyon
Language
EN