Movatterモバイル変換

Property	Value
dbo:abstract	Seq2seq is a family of machine learning approaches used for natural language processing. Applications include language translation, image captioning, conversational models and text summarization. (en) Seq2Seq（Sequence to sequence）模型，是将序列（Sequence）映射到序列的神經網絡機器學習模型。這個模型最初設計用於改進機器翻譯技術，可容許機器通過此模型發現及學習將一種語言的語句（詞語序列）映射到另一種語言的對應語句上。除此之外，Seq2Seq也能廣泛地應用到各種不同的技術上，如聊天機器人、Inbox by Gmail等，但需要有配對好的文本集才能訓練出對應的模型。 Seq2seq是用于自然语言处理的一系列机器学习方法。应用领域包括机器翻译，图像描述，对话模型和文本摘要。 (zh)
dbo:wikiPageExternalLink	https://blog.keras.io/a-ten-minute-introduction-to-sequence-to-sequence-learning-in-keras.html%7Ctitle=A https://towardsdatascience.com/day-1-2-attention-seq2seq-models-65df3f49e263%7Ctitle=Attention https://medium.com/@devnag/seq2seq-the-clown-car-of-deep-learning-f88e1204dac3%7Ctitle=seq2seq:
dbo:wikiPageID	62607005 (xsd:integer)
dbo:wikiPageLength	7394 (xsd:nonNegativeInteger)
dbo:wikiPageRevisionID	1124279879 (xsd:integer)
dbo:wikiPageWikiLink	dbr:Natural_language_processing dbr:Vanishing_gradient_problem dbr:Symbolic_integration dbr:Gated_recurrent_unit dbr:Equation_solving dbr:GPT-2 dbr:Conversational_model dbr:Theano_(software) dbr:MATLAB dbr:Machine_learning dbr:Pattern_recognition dbr:Torch_(machine_learning) dbr:GPT-3 dbr:Language_model dbr:Amazon_(company) dbr:Facebook dbr:Noise_reduction dbr:Chatbot dbr:Differential_equation dbr:Recurrent_neural_network dbr:Attention_(machine_learning) dbr:TensorFlow dbr:Artificial_neural_network dbc:Artificial_neural_networks dbc:Google_software dbc:Natural_language_processing dbr:Maple_(software) dbr:Softmax_function dbr:Image_captioning dbr:Bucket_(computing) dbr:OpenAI dbr:Wolfram_Mathematica dbr:Long_short-term_memory dbr:Loss_function dbr:Machine_translation dbr:Sequence_transformation dbr:Text_summarization dbr:Beam_Search dbr:Parameter_(machine_learning) dbr:Language_translation
dbp:wikiPageUsesTemplate	dbt:Cite_arXiv dbt:Cite_web dbt:Reflist dbt:Short_description
dcterms:subject	dbc:Artificial_neural_networks dbc:Google_software dbc:Natural_language_processing
rdfs:comment	Seq2seq is a family of machine learning approaches used for natural language processing. Applications include language translation, image captioning, conversational models and text summarization. (en) Seq2Seq（Sequence to sequence）模型，是将序列（Sequence）映射到序列的神經網絡機器學習模型。這個模型最初設計用於改進機器翻譯技術，可容許機器通過此模型發現及學習將一種語言的語句（詞語序列）映射到另一種語言的對應語句上。除此之外，Seq2Seq也能廣泛地應用到各種不同的技術上，如聊天機器人、Inbox by Gmail等，但需要有配對好的文本集才能訓練出對應的模型。 Seq2seq是用于自然语言处理的一系列机器学习方法。应用领域包括机器翻译，图像描述，对话模型和文本摘要。 (zh)
rdfs:label	Seq2seq (en) Seq2Seq模型 (zh)
owl:sameAs	wikidata:Seq2seq dbpedia-vi:Seq2seq dbpedia-zh:Seq2seq https://global.dbpedia.org/id/3reik
prov:wasDerivedFrom	wikipedia-en:Seq2seq?oldid=1124279879&ns=0
foaf:homepage	http://blog.keras.io
foaf:isPrimaryTopicOf	wikipedia-en:Seq2seq
isdbo:knownFor of	dbr:Oriol_Vinyals
isdbo:wikiPageWikiLink of	dbr:Natural_language_processing dbr:Link_prediction dbr:Oriol_Vinyals dbr:Long_short-term_memory dbr:Syntactic_parsing_(computational_linguistics) dbr:Paraphrasing_(computational_linguistics)
isdbp:knownFor of	dbr:Oriol_Vinyals
isrdfs:seeAlso of	dbr:Syntactic_parsing_(computational_linguistics)
isfoaf:primaryTopic of	wikipedia-en:Seq2seq

Movatterモバイル変換

About:Seq2seq