Transformer for Machine Learning: A Deep Dive

Jupyter notebooks

Chapter	Area	Application	Architecture
2	Text	Machine translation, LSTM vs. Transformer	Transformer (original)
3	Text	Sentiment classification	RoBERTa
	Text	Topic Modeling	BERT
4	Text	Multilingual sentiment classification	USEm
5	Text	Sentiment and attention weights	T5
6	Speech	Automatic speech recognition	Speech2Text2, HuBERT
7	Medical Text, XAI	Medical text classification	BERT, Bio_Clinical BERT

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
img		img
Chapter-2-Machine-Translation.ipynb		Chapter-2-Machine-Translation.ipynb
Chapter-3-RoBERTa_SentimentClassification.ipynb		Chapter-3-RoBERTa_SentimentClassification.ipynb
Chapter-3-TopicModeling.ipynb		Chapter-3-TopicModeling.ipynb
Chapter-4-multilingual-sentiment-classification-with-USEm.ipynb		Chapter-4-multilingual-sentiment-classification-with-USEm.ipynb
Chapter-5-T5-sentiment-and-attention.ipynb		Chapter-5-T5-sentiment-and-attention.ipynb
Chapter-6-Transformer-for-ASR.ipynb		Chapter-6-Transformer-for-ASR.ipynb
Chapter-7-Transformer-Classifier-Explainability.ipynb		Chapter-7-Transformer-Classifier-Explainability.ipynb
README.md		README.md
reviews.csv		reviews.csv