SpringerNLP/Chapter11
Chapter 11: Transfer Learning/Domain Adaptation
This project helps researchers and students understand and apply transfer learning and domain adaptation techniques to text data. By inputting the Amazon Review dataset, it demonstrates how models can learn from one domain and adapt to another, providing insights into improving model performance with limited data. This is ideal for those studying natural language processing or machine learning, particularly in academic or research settings.
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Use this if you are an NLP student or researcher wanting to see practical examples of transfer learning and domain adaptation on real-world text data.
Not ideal if you need a production-ready solution or a tool for immediate application to your own custom datasets without significant modification.
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Jupyter Notebook
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Last pushed
Jul 23, 2019
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