Chapter: Language and modeling

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Home > Supervised Machine Learning for Text Analysis in R > Language and modeling

Supervised Machine Learning for Text Analysis in R |

Emil Hvitfeldt; Julia Silge

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Supervised Machine Learning for Text Analysis in R

Language and modeling

Chapter Info

Authors

Emil Hvitfeldt; Julia Silge

ARI Id

1665707105579_13494086

Access

Not Available Free

Pages

3-8

DOI

10.1201/9781003093459-2

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Chapters/Headings	Author(s)	Pages	Info
Natural Language Features		1-98
Language and modeling	Emil Hvitfeldt; Julia Silge	3-8
Tokenization	Emil Hvitfeldt; Julia Silge	9-36
Stop words	Emil Hvitfeldt; Julia Silge	37-52
Stemming	Emil Hvitfeldt; Julia Silge	53-72
Word Embeddings	Emil Hvitfeldt; Julia Silge	73-98
Machine Learning Methods		99-222
Overview	Emil Hvitfeldt; Julia Silge	100-104
Regression	Emil Hvitfeldt; Julia Silge	105-154
Classification	Emil Hvitfeldt; Julia Silge	155-222
Deep Learning Methods		223-342
Overview	Emil Hvitfeldt; Julia Silge	224-230
Dense neural networks	Emil Hvitfeldt; Julia Silge	231-272
Long short-term memory (LSTM) networks	Emil Hvitfeldt; Julia Silge	273-302
Convolutional neural networks	Emil Hvitfeldt; Julia Silge	303-342
Conclusion		343-346
Text models in the real world	Emil Hvitfeldt; Julia Silge	344-346
Chapters/Headings	Author(s)	Pages	Info

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