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Hybrid-Approach-To-Depression-Detection

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This repository applies Deep Learning techniques for depression detection in text, using LSTM, GRU, BiLSTM, BERT models, and a baseline FFNN. It also includes data visualizations, autoencoder semantics, KMeans clustering, and detailed performance comparisons.

Creat2023-07-12T14:23:30
Update2025-06-11T19:50:33
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