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种子哈希：0448a60d7dd447b48478a3aba6fc4c076adee970
文档大小：1.6 GB
文档个数：89个文档
下载次数：4280次
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收录时间：2018-09-26
最近下载：2025-05-16
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文档列表

001.Introduction to NLP and our course/001. About this course.mp4 13.2 MB
001.Introduction to NLP and our course/001. About this course.srt 3.3 kB
001.Introduction to NLP and our course/002. Welcome video.mp4 21.0 MB
001.Introduction to NLP and our course/002. Welcome video.srt 7.4 kB
001.Introduction to NLP and our course/003. Main approaches in NLP.mp4 31.5 MB
001.Introduction to NLP and our course/003. Main approaches in NLP.srt 9.8 kB
001.Introduction to NLP and our course/004. Brief overview of the next weeks.mp4 27.4 MB
001.Introduction to NLP and our course/004. Brief overview of the next weeks.srt 9.7 kB
001.Introduction to NLP and our course/005. [Optional] Linguistic knowledge in NLP.mp4 36.7 MB
001.Introduction to NLP and our course/005. [Optional] Linguistic knowledge in NLP.srt 13.0 kB
002.How to from plain texts to their classification/006. Text preprocessing.mp4 53.7 MB
002.How to from plain texts to their classification/006. Text preprocessing.srt 20.7 kB
002.How to from plain texts to their classification/007. Feature extraction from text.mp4 50.6 MB
002.How to from plain texts to their classification/007. Feature extraction from text.srt 18.8 kB
002.How to from plain texts to their classification/008. Linear models for sentiment analysis.mp4 37.9 MB
002.How to from plain texts to their classification/008. Linear models for sentiment analysis.srt 12.9 kB
002.How to from plain texts to their classification/009. Hashing trick in spam filtering.mp4 64.2 MB
002.How to from plain texts to their classification/009. Hashing trick in spam filtering.srt 23.4 kB
003.Simple deep learning for text classification/010. Neural networks for words.mp4 53.1 MB
003.Simple deep learning for text classification/010. Neural networks for words.srt 19.5 kB
003.Simple deep learning for text classification/011. Neural networks for characters.mp4 29.3 MB
003.Simple deep learning for text classification/011. Neural networks for characters.srt 10.7 kB
004.Language modeling it's all about counting!/012. Count! N-gram language models.mp4 35.5 MB
004.Language modeling it's all about counting!/012. Count! N-gram language models.srt 13.9 kB
004.Language modeling it's all about counting!/013. Perplexity is our model surprised with a real text.mp4 28.1 MB
004.Language modeling it's all about counting!/013. Perplexity is our model surprised with a real text.srt 10.6 kB
004.Language modeling it's all about counting!/014. Smoothing what if we see new n-grams.mp4 28.6 MB
004.Language modeling it's all about counting!/014. Smoothing what if we see new n-grams.srt 9.5 kB
005.Sequence tagging with probabilistic models/015. Hidden Markov Models.mp4 51.8 MB
005.Sequence tagging with probabilistic models/015. Hidden Markov Models.srt 17.0 kB
005.Sequence tagging with probabilistic models/016. Viterbi algorithm what are the most probable tags.mp4 41.2 MB
005.Sequence tagging with probabilistic models/016. Viterbi algorithm what are the most probable tags.srt 13.4 kB
005.Sequence tagging with probabilistic models/017. MEMMs, CRFs and other sequential models for Named Entity Recognition.mp4 43.7 MB
005.Sequence tagging with probabilistic models/017. MEMMs, CRFs and other sequential models for Named Entity Recognition.srt 14.8 kB
006.Deep Learning for the same tasks/018. Neural Language Models.mp4 33.0 MB
006.Deep Learning for the same tasks/018. Neural Language Models.srt 12.1 kB
006.Deep Learning for the same tasks/019. Whether you need to predict a next word or a label - LSTM is here to help!.mp4 45.0 MB
006.Deep Learning for the same tasks/019. Whether you need to predict a next word or a label - LSTM is here to help!.srt 15.3 kB
007.Word and sentence embeddings/020. Distributional semantics bee and honey vs. bee an bumblebee.mp4 29.6 MB
007.Word and sentence embeddings/020. Distributional semantics bee and honey vs. bee an bumblebee.srt 11.3 kB
007.Word and sentence embeddings/021. Explicit and implicit matrix factorization.mp4 48.0 MB
007.Word and sentence embeddings/021. Explicit and implicit matrix factorization.srt 15.8 kB
007.Word and sentence embeddings/022. Word2vec and doc2vec (and how to evaluate them).mp4 41.4 MB
007.Word and sentence embeddings/022. Word2vec and doc2vec (and how to evaluate them).srt 13.0 kB
007.Word and sentence embeddings/023. Word analogies without magic king man + woman != queen.mp4 42.0 MB
007.Word and sentence embeddings/023. Word analogies without magic king man + woman != queen.srt 13.1 kB
007.Word and sentence embeddings/024. Why words From character to sentence embeddings.mp4 44.8 MB
007.Word and sentence embeddings/024. Why words From character to sentence embeddings.srt 15.0 kB
008.Topic models/025. Topic modeling a way to navigate through text collections.mp4 27.2 MB
008.Topic models/025. Topic modeling a way to navigate through text collections.srt 9.1 kB
008.Topic models/026. How to train PLSA.mp4 24.7 MB
008.Topic models/026. How to train PLSA.srt 8.8 kB
008.Topic models/027. The zoo of topic models.mp4 53.8 MB
008.Topic models/027. The zoo of topic models.srt 17.3 kB
009.Statistical Machine Translation/028. Introduction to Machine Translation.mp4 59.9 MB
009.Statistical Machine Translation/028. Introduction to Machine Translation.srt 19.3 kB
009.Statistical Machine Translation/029. Noisy channel said in English, received in French.mp4 22.7 MB
009.Statistical Machine Translation/029. Noisy channel said in English, received in French.srt 7.7 kB
009.Statistical Machine Translation/030. Word Alignment Models.mp4 45.2 MB
009.Statistical Machine Translation/030. Word Alignment Models.srt 15.8 kB
010.Encoder-decoder-attention arhitecture/031. Encoder-decoder architecture.mp4 23.5 MB
010.Encoder-decoder-attention arhitecture/031. Encoder-decoder architecture.srt 8.3 kB
010.Encoder-decoder-attention arhitecture/032. Attention mechanism.mp4 32.7 MB
010.Encoder-decoder-attention arhitecture/032. Attention mechanism.srt 12.4 kB
010.Encoder-decoder-attention arhitecture/033. How to deal with a vocabulary.mp4 42.0 MB
010.Encoder-decoder-attention arhitecture/033. How to deal with a vocabulary.srt 14.8 kB
010.Encoder-decoder-attention arhitecture/034. How to implement a conversational chat-bot.mp4 40.0 MB
010.Encoder-decoder-attention arhitecture/034. How to implement a conversational chat-bot.srt 14.5 kB
011.Summarization and simplification tasks/035. Sequence to sequence learning one-size fits all.mp4 38.5 MB
011.Summarization and simplification tasks/035. Sequence to sequence learning one-size fits all.srt 13.7 kB
011.Summarization and simplification tasks/036. Get to the point! Summarization with pointer-generator networks.mp4 43.0 MB
011.Summarization and simplification tasks/036. Get to the point! Summarization with pointer-generator networks.srt 15.7 kB
012.Natural Language Understanding (NLU)/037. Task-oriented dialog systems.mp4 44.3 MB
012.Natural Language Understanding (NLU)/037. Task-oriented dialog systems.srt 17.6 kB
012.Natural Language Understanding (NLU)/038. Intent classifier and slot tagger (NLU).mp4 50.3 MB
012.Natural Language Understanding (NLU)/038. Intent classifier and slot tagger (NLU).srt 18.9 kB
012.Natural Language Understanding (NLU)/039. Adding context to NLU.mp4 17.9 MB
012.Natural Language Understanding (NLU)/039. Adding context to NLU.srt 7.1 kB
012.Natural Language Understanding (NLU)/040. Adding lexicon to NLU.mp4 29.7 MB
012.Natural Language Understanding (NLU)/040. Adding lexicon to NLU.srt 10.3 kB
013.Dialog Manager (DM)/041. State tracking in DM.mp4 47.1 MB
013.Dialog Manager (DM)/041. State tracking in DM.srt 17.9 kB
013.Dialog Manager (DM)/042. Policy optimisation in DM.mp4 28.4 MB
013.Dialog Manager (DM)/042. Policy optimisation in DM.srt 10.3 kB
013.Dialog Manager (DM)/043. Final remarks.mp4 22.7 MB
013.Dialog Manager (DM)/043. Final remarks.srt 7.6 kB
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