Deep Learning for Natural Language Processing (MEAP V07)
Stephan Raaijmakers
Manning Early Access Program (MEAP) Version 07
chapters 1 to 8
Deep Learning for Natural Language Processing teaches you to apply state-of-the-art deep learning approaches to natural language processing tasks. You’ll learn key NLP concepts like neural word embeddings, auto-encoders, part-of-speech tagging, parsing, and semantic inference. Then you’ll dive deeper into advanced topics including deep memory-based NLP, linguistic structure, and hyperparameters for deep NLP. Along the way, you’ll pick up emerging best practices and gain hands-on experience with a myriad of examples, all written in Python and the powerful Keras library. By the time you’re done reading this invaluable book, you’ll be solving a wide variety of NLP problems with cutting-edge deep learning techniques!
chapters 1 to 8
Deep Learning for Natural Language Processing teaches you to apply state-of-the-art deep learning approaches to natural language processing tasks. You’ll learn key NLP concepts like neural word embeddings, auto-encoders, part-of-speech tagging, parsing, and semantic inference. Then you’ll dive deeper into advanced topics including deep memory-based NLP, linguistic structure, and hyperparameters for deep NLP. Along the way, you’ll pick up emerging best practices and gain hands-on experience with a myriad of examples, all written in Python and the powerful Keras library. By the time you’re done reading this invaluable book, you’ll be solving a wide variety of NLP problems with cutting-edge deep learning techniques!
年:
2020
出版:
MEAP
出版社:
Manning Publications
语言:
english
页:
266
ISBN 10:
1617295442
ISBN 13:
9781617295447
文件:
PDF, 10.25 MB
IPFS:
,
english, 2020
Amazon 
Barnes & Noble 
Bookshop.org 
转换文件
更多搜索结果
其他特权 ![Edward Raff — Inside Deep Learning: Math, Algorithms, Models [MEAP]](https://s3proxy.cdn-zlib.se/covers200/collections/genesis/73c62922876cddf60f02514d4326ee904d7f5df2ab329ddc3ae2d44ef921acc5.jpg)
关键词
关联书单
