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Supervised Machine Learning for Text Analysis in R
Taschenbuch von Emil Hvitfeldt (u. a.)
Sprache: Englisch

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Beschreibung

This book is designed to provide practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate text into their modeling pipelines. We assume that the reader is somewhat familiar with R, predictive modeling concepts for non-text data, and the tidyverse family of packages.

This book is designed to provide practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate text into their modeling pipelines. We assume that the reader is somewhat familiar with R, predictive modeling concepts for non-text data, and the tidyverse family of packages.

Über den Autor

Emil Hvitfeldt is a clinical data analyst working in healthcare, and an adjunct professor at American University where he is teaching statistical machine learning with tidymodels. He is also an open source R developer and author of the textrecipes package.

Julia Silge is a data scientist and software engineer at RStudio PBC where she works on open source modeling tools. She is an author, an international keynote speaker and educator, and a real-world practitioner focusing on data analysis and machine learning practice.

Inhaltsverzeichnis

1. Language and modeling. 2. Tokenization. 3. Stop words. 4. Stemming. 5. Word Embeddings. 6. Regression. 7. Classification. 8. Dense neural networks. 9. Long short-term memory (LSTM) networks. 10. Convolutional neural networks.

Details
Erscheinungsjahr: 2021
Genre: Umwelt
Produktart: Nachschlagewerke
Rubrik: Ökologie
Medium: Taschenbuch
Seiten: 402
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780367554194
ISBN-10: 0367554194
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Hvitfeldt, Emil
Silge, Julia
Hersteller: Taylor & Francis Ltd
Maße: 231 x 152 x 23 mm
Von/Mit: Emil Hvitfeldt (u. a.)
Erscheinungsdatum: 22.10.2021
Gewicht: 0,606 kg
preigu-id: 125336492
Über den Autor

Emil Hvitfeldt is a clinical data analyst working in healthcare, and an adjunct professor at American University where he is teaching statistical machine learning with tidymodels. He is also an open source R developer and author of the textrecipes package.

Julia Silge is a data scientist and software engineer at RStudio PBC where she works on open source modeling tools. She is an author, an international keynote speaker and educator, and a real-world practitioner focusing on data analysis and machine learning practice.

Inhaltsverzeichnis

1. Language and modeling. 2. Tokenization. 3. Stop words. 4. Stemming. 5. Word Embeddings. 6. Regression. 7. Classification. 8. Dense neural networks. 9. Long short-term memory (LSTM) networks. 10. Convolutional neural networks.

Details
Erscheinungsjahr: 2021
Genre: Umwelt
Produktart: Nachschlagewerke
Rubrik: Ökologie
Medium: Taschenbuch
Seiten: 402
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780367554194
ISBN-10: 0367554194
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Hvitfeldt, Emil
Silge, Julia
Hersteller: Taylor & Francis Ltd
Maße: 231 x 152 x 23 mm
Von/Mit: Emil Hvitfeldt (u. a.)
Erscheinungsdatum: 22.10.2021
Gewicht: 0,606 kg
preigu-id: 125336492
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