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Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
GloVe.
Provides a comprehensive overview of deep learning and transformers, with a focus on their applications in NLP tasks such as text classification, machine translation, and question answering. It valuable resource for researchers and practitioners who want to gain a deep understanding of transformers and their use in NLP.
Provides a comprehensive overview of deep learning techniques for NLP. It covers a wide range of topics, including word embeddings, recurrent neural networks, convolutional neural networks, and attention mechanisms. It valuable resource for researchers and practitioners who want to gain a deep understanding of deep learning for NLP.
Provides a comprehensive overview of statistical machine translation. It covers a wide range of topics, including machine translation models, training algorithms, and evaluation metrics. It valuable resource for researchers and practitioners who want to gain a deep understanding of statistical machine translation.
Provides a comprehensive overview of neural machine translation. It covers a wide range of topics, including neural machine translation models, training algorithms, and evaluation metrics. It valuable resource for researchers and practitioners who want to gain a deep understanding of neural machine translation.
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including deep learning models, training algorithms, and evaluation metrics. It valuable resource for researchers and practitioners who want to gain a deep understanding of deep learning.
Provides a comprehensive overview of machine learning. It covers a wide range of topics, including machine learning models, training algorithms, and evaluation metrics. It valuable resource for researchers and practitioners who want to gain a deep understanding of machine learning.
Provides a comprehensive overview of natural language processing. It covers a wide range of topics, including natural language processing models, training algorithms, and evaluation metrics. It valuable resource for researchers and practitioners who want to gain a deep understanding of natural language processing.
Provides a comprehensive overview of speech and language processing. It covers a wide range of topics, including speech recognition, natural language processing, and machine translation. It valuable resource for researchers and practitioners who want to gain a deep understanding of speech and language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/802bh7/glov
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