Transfer Learning for Natural Language Processing

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Transfer Learning for Natural Language Processing
English | 2021 | ISBN: 1617297267 | 376 Pages | EPUB | 5.42 MB
Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You'll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you'll save on training time and computational costs.

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