LinkedIn Learning - Introduction to NLP Using R

Files Included :

01 - Welcome to natural language processing with R.mp4 (16.69 MB)
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02 - Skills and tools you'll need to be successful in this course.mp4 (8.49 MB)
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01 - What is tm and why do you need it.mp4 (10.93 MB)
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02 - tm documentation walk-through.mp4 (11.84 MB)
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03 - Real-world NLP with tm.mp4 (19.89 MB)
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04 - Real-world NLP with quanteda.mp4 (16.37 MB)
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05 - Real-world NLP with tidytext.mp4 (13.4 MB)
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01 - Understanding corpora and sources.mp4 (9.55 MB)
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02 - Examining corpora.mp4 (17.97 MB)
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03 - Examining sources.mp4 (31.46 MB)
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04 - Custom sources.mp4 (7.66 MB)
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05 - Combining and subsetting corpora.mp4 (21.27 MB)
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01 - Working with document metadata.mp4 (34.39 MB)
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02 - Make useful metadata.mp4 (26.17 MB)
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03 - Finding and filtering based on metadata.mp4 (22.51 MB)
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01 - Transformations.mp4 (16.22 MB)
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02 - Stop words.mp4 (16.11 MB)
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03 - Stemming.mp4 (15.1 MB)
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04 - Lemmatization.mp4 (14.76 MB)
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05 - Tokenization.mp4 (15.95 MB)
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06 - Ngrams.mp4 (25.34 MB)
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07 - Part of speech tagging.mp4 (17.86 MB)
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01 - Understanding the document-term matrix.mp4 (14.74 MB)
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02 - Create the document-term matrix.mp4 (22.34 MB)
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03 - Weighting the document-term matrix.mp4 (17.11 MB)
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04 - Focus the document-term matrix.mp4 (17.84 MB)
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01 - Word and document frequency.mp4 (14.41 MB)
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02 - Hierarchical clustering.mp4 (12.54 MB)
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03 - Associated terms.mp4 (16.12 MB)
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01 - What is sentiment analysis.mp4 (11.51 MB)
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02 - Real-world example of sentiment analysis.mp4 (24.22 MB)
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03 - Sentiment datasets.mp4 (20.86 MB)
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04 - Sentiment tools.mp4 (12.92 MB)
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01 - Plotting text mining.mp4 (15.74 MB)
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02 - Plotting Zipf's and Heap's Law.mp4 (8.25 MB)
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03 - Word clouds.mp4 (9.48 MB)
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01 - Your next steps in NLP.mp4 (26.3 MB)
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