Here we apply deep learning approaches to accurately identify 30 common bacterial pathogens, reaching an average isolate-level accuracy exceeding 78%, and an antibiotic treatment identification acc…
In this project, we propose a Deep Learning architecture for Sarcasm Detection, while utilizing pre-trained Word Embeddings from three well-known models: Word2Vec, fastText and Glove.
The task of the assignment 4 is Transfer Learning using a CNN pretrained on IMAGENET.
19 contributions in the last year
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