Neural Network Methods in Natural Language Processing

Yoav Goldberg, Graeme Hirst

Informasi Dasar

62 kali
21.01.682
006.32
Buku - Circulation (Dapat Dipinjam)
4

The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.

The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

Subjek

NEURAL NETWORKS
 

Katalog

Neural Network Methods in Natural Language Processing
978-1627052986
xxii, 287p.: ill.; 25 cm
English

Sirkulasi

Rp. 0
Rp. 1.000
Ya

Pengarang

Yoav Goldberg, Graeme Hirst
Perorangan
 
 

Penerbit

Morgan, Claypool Publishers
New York
1971

Koleksi

Kompetensi

  • CPI4G3 - PENGOLAHAN BAHASA ALAMI

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