FreeCoursesOnline Me Coursera Natural Language Processing | 0448A60D7DD447B48478A3ABA6FC4C076ADEE970

FreeCoursesOnline Me Coursera Natural Language Processing

Name	[FreeCoursesOnline.Me] Coursera - Natural Language Processing	DOWNLOAD Copy Link
Total Size	1.6 GB
Total Files	89
Last Seen	2024-09-20 01:58
Hash	0448A60D7DD447B48478A3ABA6FC4C076ADEE970

/001.Introduction to NLP and our course/
001. About this course.mp4	13.2 MB
001. About this course.srt	3.3 KB
002. Welcome video.mp4	21.0 MB
002. Welcome video.srt	7.4 KB
003. Main approaches in NLP.mp4	31.5 MB
003. Main approaches in NLP.srt	9.8 KB
004. Brief overview of the next weeks.mp4	27.4 MB
004. Brief overview of the next weeks.srt	9.7 KB
005. [Optional] Linguistic knowledge in NLP.mp4	36.7 MB
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
006. Text preprocessing.srt	20.7 KB
007. Feature extraction from text.mp4	50.6 MB
007. Feature extraction from text.srt	18.8 KB
008. Linear models for sentiment analysis.mp4	37.9 MB
008. Linear models for sentiment analysis.srt	12.9 KB
009. Hashing trick in spam filtering.mp4	64.2 MB
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
010. Neural networks for words.srt	19.5 KB
011. Neural networks for characters.mp4	29.3 MB
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
012. Count! N-gram language models.srt	13.9 KB
013. Perplexity is our model surprised with a real text.mp4	28.1 MB
013. Perplexity is our model surprised with a real text.srt	10.6 KB
014. Smoothing what if we see new n-grams.mp4	28.6 MB
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
015. Hidden Markov Models.srt	17.0 KB
016. Viterbi algorithm what are the most probable tags.mp4	41.2 MB
016. Viterbi algorithm what are the most probable tags.srt	13.4 KB
017. MEMMs, CRFs and other sequential models for Named Entity Recognition.mp4	43.7 MB
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
018. Neural Language Models.srt	12.1 KB
019. Whether you need to predict a next word or a label - LSTM is here to help!.mp4	45.0 MB
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
020. Distributional semantics bee and honey vs. bee an bumblebee.srt	11.3 KB
021. Explicit and implicit matrix factorization.mp4	48.0 MB
021. Explicit and implicit matrix factorization.srt	15.8 KB
022. Word2vec and doc2vec (and how to evaluate them).mp4	41.4 MB
022. Word2vec and doc2vec (and how to evaluate them).srt	13.0 KB
023. Word analogies without magic king man + woman != queen.mp4	42.0 MB
023. Word analogies without magic king man + woman != queen.srt	13.1 KB
024. Why words From character to sentence embeddings.mp4	44.8 MB
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
025. Topic modeling a way to navigate through text collections.srt	9.1 KB
026. How to train PLSA.mp4	24.7 MB
026. How to train PLSA.srt	8.8 KB
027. The zoo of topic models.mp4	53.8 MB
027. The zoo of topic models.srt	17.3 KB
/009.Statistical Machine Translation/
028. Introduction to Machine Translation.mp4	59.9 MB
028. Introduction to Machine Translation.srt	19.3 KB
029. Noisy channel said in English, received in French.mp4	22.7 MB
029. Noisy channel said in English, received in French.srt	7.7 KB
030. Word Alignment Models.mp4	45.2 MB
030. Word Alignment Models.srt	15.8 KB
/010.Encoder-decoder-attention arhitecture/
031. Encoder-decoder architecture.mp4	23.5 MB
031. Encoder-decoder architecture.srt	8.3 KB
032. Attention mechanism.mp4	32.7 MB
032. Attention mechanism.srt	12.4 KB
033. How to deal with a vocabulary.mp4	42.0 MB
033. How to deal with a vocabulary.srt	14.8 KB
034. How to implement a conversational chat-bot.mp4	40.0 MB
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
035. Sequence to sequence learning one-size fits all.srt	13.7 KB
036. Get to the point! Summarization with pointer-generator networks.mp4	43.0 MB
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
037. Task-oriented dialog systems.srt	17.6 KB
038. Intent classifier and slot tagger (NLU).mp4	50.3 MB
038. Intent classifier and slot tagger (NLU).srt	18.9 KB
039. Adding context to NLU.mp4	17.9 MB
039. Adding context to NLU.srt	7.1 KB
040. Adding lexicon to NLU.mp4	29.7 MB
040. Adding lexicon to NLU.srt	10.3 KB
/013.Dialog Manager (DM)/
041. State tracking in DM.mp4	47.1 MB
041. State tracking in DM.srt	17.9 KB
042. Policy optimisation in DM.mp4	28.4 MB
042. Policy optimisation in DM.srt	10.3 KB
043. Final remarks.mp4	22.7 MB
043. Final remarks.srt	7.6 KB
/
[FreeCoursesOnline.Me].url	0.1 KB
[FreeTutorials.Us].url	0.1 KB
[FTU Forum].url	0.3 KB
Total files 89