Deep learning: a practitioner's approach
How can machine learning--especially deep neural networks--make a real difference in your organization? This hands-on guide not only provides practical information, but helps you get started building efficient deep learning networks. The authors provide the fundamentals of deep learning--tuning, par...
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Sebastopol, CA
O'Reilly Media, Inc.
2017
|
| Ausgabe: | First edition. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781491924570/?ar |
| Zusammenfassung: | How can machine learning--especially deep neural networks--make a real difference in your organization? This hands-on guide not only provides practical information, but helps you get started building efficient deep learning networks. The authors provide the fundamentals of deep learning--tuning, parallelization, vectorization, and building pipelines--that are valid for any library before introducing the open source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you'll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. |
| Beschreibung: | Includes index. - Online resource; title from PDF title page (EBSCO, viewed August 24, 2017) |
| Umfang: | 1 Online-Ressource (507 Seiten) color illustrations |
| ISBN: | 9781491914236 1491914238 9781491914212 1491914211 9781491924570 |
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| spelling | Patterson, Josh VerfasserIn aut Deep learning a practitioner's approach Josh Patterson and Adam Gibson First edition. Sebastopol, CA O'Reilly Media, Inc. 2017 ©2017 1 Online-Ressource (507 Seiten) color illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes index. - Online resource; title from PDF title page (EBSCO, viewed August 24, 2017) How can machine learning--especially deep neural networks--make a real difference in your organization? This hands-on guide not only provides practical information, but helps you get started building efficient deep learning networks. The authors provide the fundamentals of deep learning--tuning, parallelization, vectorization, and building pipelines--that are valid for any library before introducing the open source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you'll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Machine learning Artificial intelligence Neural networks (Computer science) Artificial Intelligence Neural Networks, Computer Machine Learning Apprentissage automatique Intelligence artificielle Réseaux neuronaux (Informatique) artificial intelligence COMPUTERS ; General Gibson, Adam 1989- VerfasserIn aut 1491914254 Erscheint auch als Druck-Ausgabe 1491914254 |
| spellingShingle | Patterson, Josh Gibson, Adam 1989- Deep learning a practitioner's approach Machine learning Artificial intelligence Neural networks (Computer science) Artificial Intelligence Neural Networks, Computer Machine Learning Apprentissage automatique Intelligence artificielle Réseaux neuronaux (Informatique) artificial intelligence COMPUTERS ; General |
| title | Deep learning a practitioner's approach |
| title_auth | Deep learning a practitioner's approach |
| title_exact_search | Deep learning a practitioner's approach |
| title_full | Deep learning a practitioner's approach Josh Patterson and Adam Gibson |
| title_fullStr | Deep learning a practitioner's approach Josh Patterson and Adam Gibson |
| title_full_unstemmed | Deep learning a practitioner's approach Josh Patterson and Adam Gibson |
| title_short | Deep learning |
| title_sort | deep learning a practitioner s approach |
| title_sub | a practitioner's approach |
| topic | Machine learning Artificial intelligence Neural networks (Computer science) Artificial Intelligence Neural Networks, Computer Machine Learning Apprentissage automatique Intelligence artificielle Réseaux neuronaux (Informatique) artificial intelligence COMPUTERS ; General |
| topic_facet | Machine learning Artificial intelligence Neural networks (Computer science) Artificial Intelligence Neural Networks, Computer Machine Learning Apprentissage automatique Intelligence artificielle Réseaux neuronaux (Informatique) artificial intelligence COMPUTERS ; General |
| work_keys_str_mv | AT pattersonjosh deeplearningapractitionersapproach AT gibsonadam deeplearningapractitionersapproach |