Angular and Machine Learning Pocket Primer:
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic machine learning concepts and incorporate that knowledge into Angular applications. The book is intended to be a fast-paced introduction to some basic features of machine learning and an overview...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Herndon
Mercury Learning and Information
[2020]
|
| Series: | Pocket Primer
|
| Subjects: | |
| Online Access: | DE-1046 DE-1043 DE-858 DE-859 DE-860 DE-739 Volltext |
| Summary: | As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic machine learning concepts and incorporate that knowledge into Angular applications. The book is intended to be a fast-paced introduction to some basic features of machine learning and an overview of several popular machine learning classifiers. It includes code samples and numerous figures and covers topics such as Angular functionality, basic machine learning concepts, classification algorithms, TensorFlow and Keras. The files with code and color figures are on the companion disc with the book or available from the publisher. Features:Introduces the basic machine learning concepts and Angular applicationsIncludes source code and full color figures |
| Item Description: | Description based on online resource; title from PDF title page (publisher's Web site, viewed 01. Nov 2023) |
| Physical Description: | 1 Online-Ressource (262 Seiten) |
| ISBN: | 9781683924685 |
| DOI: | 10.1515/9781683924685 |
Staff View
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| isbn | 9781683924685 |
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| spelling | Campesato, Oswald Verfasser aut Angular and Machine Learning Pocket Primer Oswald Campesato Herndon Mercury Learning and Information [2020] © 2020 1 Online-Ressource (262 Seiten) txt rdacontent c rdamedia cr rdacarrier Pocket Primer Description based on online resource; title from PDF title page (publisher's Web site, viewed 01. Nov 2023) As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic machine learning concepts and incorporate that knowledge into Angular applications. The book is intended to be a fast-paced introduction to some basic features of machine learning and an overview of several popular machine learning classifiers. It includes code samples and numerous figures and covers topics such as Angular functionality, basic machine learning concepts, classification algorithms, TensorFlow and Keras. The files with code and color figures are on the companion disc with the book or available from the publisher. Features:Introduces the basic machine learning concepts and Angular applicationsIncludes source code and full color figures In English Artificial Intelligence Programming COMPUTERS / Social Aspects / Human-Computer Interaction bisacsh Erscheint auch als Druck-Ausgabe 9781683924708 https://doi.org/10.1515/9781683924685?locatt=mode:legacy Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Campesato, Oswald Angular and Machine Learning Pocket Primer Artificial Intelligence Programming COMPUTERS / Social Aspects / Human-Computer Interaction bisacsh |
| title | Angular and Machine Learning Pocket Primer |
| title_auth | Angular and Machine Learning Pocket Primer |
| title_exact_search | Angular and Machine Learning Pocket Primer |
| title_exact_search_txtP | Angular and Machine Learning Pocket Primer |
| title_full | Angular and Machine Learning Pocket Primer Oswald Campesato |
| title_fullStr | Angular and Machine Learning Pocket Primer Oswald Campesato |
| title_full_unstemmed | Angular and Machine Learning Pocket Primer Oswald Campesato |
| title_short | Angular and Machine Learning Pocket Primer |
| title_sort | angular and machine learning pocket primer |
| topic | Artificial Intelligence Programming COMPUTERS / Social Aspects / Human-Computer Interaction bisacsh |
| topic_facet | Artificial Intelligence Programming COMPUTERS / Social Aspects / Human-Computer Interaction |
| url | https://doi.org/10.1515/9781683924685?locatt=mode:legacy |
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