Complete Guide to NLP with R
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Mark Niemann-Ross
5:04:35
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01 - Welcome to natural language processing with R.mp4
01:35
02 - Skills and tools you need to be successful in this course.mp4
02:25
01 - What is tm and why do you need it.mp4
02:18
02 - Real-world NLP with tm.mp4
05:15
03 - Real-world NLP with quanteda.mp4
04:17
04 - Real-world NLP with tidytext.mp4
03:28
01 - Understanding corpora and sources.mp4
02:16
02 - Examining corpora.mp4
07:06
03 - Examining sources.mp4
07:36
04 - Custom sources.mp4
02:18
05 - Combining and subsetting corpora.mp4
05:07
01 - Working with document metadata.mp4
08:28
02 - Make useful metadata.mp4
06:04
03 - Finding and filtering based on metadata.mp4
05:28
01 - Transformations.mp4
03:52
02 - Stop words.mp4
03:54
03 - Stemming.mp4
03:38
04 - Lemmatization.mp4
03:24
05 - Tokenization.mp4
03:54
06 - N-grams.mp4
06:32
07 - Part of speech tagging.mp4
04:51
01 - Understanding the document-term matrix.mp4
03:44
02 - Create the document-term matrix.mp4
05:29
03 - Weighting the document-term matrix.mp4
03:56
04 - Focus the document-term matrix.mp4
04:13
01 - Word and document frequency.mp4
03:29
02 - Hierarchical clustering.mp4
03:20
03 - Associated terms.mp4
03:55
01 - What is sentiment analysis.mp4
02:40
02 - Real-world example of sentiment analysis.mp4
05:49
03 - Sentiment datasets.mp4
05:02
04 - Sentiment tools.mp4
03:02
01 - Plotting text mining.mp4
04:09
02 - Plotting Zipfs and Heaps Law.mp4
02:12
03 - Word clouds.mp4
02:15
01 - Your next steps in NLP.mp4
02:12
01 - Welcome to natural language processing with R.mp4
01:25
02 - Skills you need to be successful in this course.mp4
02:16
01 - How to think like tidytext.mp4
01:59
02 - An example Calculate the most popular terms in a document.mp4
03:10
03 - Tokenizing with unnest tokens( ).mp4
08:19
04 - Stopwords, punctuation, whitespace, and numbers.mp4
06:30
05 - Stemming and lemmatization.mp4
05:35
06 - Term frequency with bind tf idf( ).mp4
05:54
07 - Sentiment analysis with sentiments( ).mp4
04:44
08 - Parts of speech with parts of speech( ).mp4
04:32
09 - Import and export from other NLP packages.mp4
02:30
01 - Next steps.mp4
01:40
01 - Welcome to natural language processing with R.mp4
00:47
02 - Skills and tools you need.mp4
03:27
01 - Introduction to quanteda.mp4
01:54
02 - Install quanteda.mp4
03:03
01 - Create a quanteda corpus.mp4
05:18
02 - Create metadata with docvars.mp4
05:50
03 - Corpus subsets and groups.mp4
08:45
04 - Reshape and segment a corpus.mp4
04:16
05 - Remove lines from a corpus.mp4
01:53
01 - Corpus and tokens.mp4
03:45
02 - Remove tokens and stopwords.mp4
04:49
03 - Group tokens.mp4
05:15
04 - Stemming with tokens.mp4
03:14
01 - Corpus, tokens, and DFM.mp4
01:02
02 - Create and modify a DFM.mp4
04:40
03 - Real-world analysis with DFM.mp4
10:27
01 - The quanteda textstats package.mp4
00:39
02 - Real-world text statistics with textstats.mp4
05:44
03 - Understand the quanteda sentiment package.mp4
02:34
04 - Real-world sentiment analysis with quanteda sentiment.mp4
13:54
05 - Visualization with textplots.mp4
03:27
06 - Use dplyr with quanteda.mp4
02:35
01 - Your next steps in NLP.mp4
01:11
01 - Project introduction.mp4
04:38
02 - Project explanation.mp4
03:41
Description
Natural Language Processing is to words as Computer Vision is to pictures! Learn NLP with the R programming language. In this course, experienced technologist Mark Niemann-Ross shows you how to use the R programming language to implement natural language processing algorithms. R is uniquely adept at manipulating matrices and producing statistics, both of which are core to NLP. Learn about frameworks that you can use with NLP, as well as the importance of corpora and sources. Find out how to work with NLP metadata and preprocess text in preparation for NLP. Explore creating structured data, applying statistics to text, and performing sentiment analysis, and then dive into visualizing NLP. Discover ways to use tidytext and quanteda R for NLP. Build your understanding of corpora, tokens, and document-feature matrix (DFM). Plus, go over analysis and visualization.
This course was created by Mark Niemann-Ross. We are pleased to host this training in our library.
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Mark Niemann-Ross
Instructor's CoursesI’m friends with technology. But I’m not blindly in love with it. I ask it questions. I explain it.
I prioritize people over technology. Bigger, better, and faster features make shinier products, but that isn’t what people want. People don’t want widgets, they want elegance and relevance.
I’m an educator, manager, evangelist, marketer, technologist, futurist, coder.
I point to the future. I explain the present. I learn from the past.
People speak different languages: marketing, sales, engineering, management, strategy. I’m fluent in all of those.
Sometimes I’m abrupt. Sometimes I apologize. I’m passionate, but willing to believe I’m wrong. I try to inform myself.
“Why” is my favorite question, followed by “When.”
I write science fiction. Sometimes it’s about spaceships, sometimes it’s about products. The goal is the same; explain where we want to be, point out hazards, celebrate arrival.
I’m engaging. Informed. Opinionated. Respectful.
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- language english
- Training sessions 73
- duration 5:04:35
- English subtitles has
- Release Date 2024/12/06
