Practical deep learning for cloud, mobile, and edge: real-world AI and computer vision projects using Python, Keras and TensorFlow
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Beijing
O'Reilly
2019
|
| Ausgabe: | First edition |
| Schlagwörter: | |
| Links: | https://ebookcentral.proquest.com/lib/th-deggendorf/detail.action?docID=5945145 https://ebookcentral.proquest.com/lib/htw-berlin/detail.action?docID=5945145 |
| Beschreibung: | Includes index |
| Umfang: | 1 Online-Ressource (viii, 585 Seiten) |
| ISBN: | 9781492034810 |
Internformat
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| 245 | 1 | 0 | |a Practical deep learning for cloud, mobile, and edge |b real-world AI and computer vision projects using Python, Keras and TensorFlow |c Anirudh Koul, Siddha Ganju, and Meher Kasam |
| 246 | 1 | 0 | |a Real-world AI and computer-vision projects using Python, Keras, and TensorFlow |
| 250 | |a First edition | ||
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| 500 | |a Includes index | ||
| 505 | 8 | |a Exploring the landscape of Artificial Intelligence -- What's in the picture: image classification with Keras -- Cats versus dogs: transfer learning in 30 lines with Keras -- Building a reverse image search engine: understanding embeddings -- From novice to master predictor: maximizing convolutional neural network accurcy -- Maximizing speed and performance of TensorFlow: a handy checklist -- Practical tools, tips, and tricks -- Cloud APIs for computer vision: up and running in 15 minutes -- Scalable inference serving on Cloud with TensorFlow Serving and KubeFlow -- AI in the browser with TensorFlow.js and mI5.js -- Real-time object classification on iOS with Core ML -- Not hotdog on iOS with Core ML and Create ML -- Shazam for food: developing android apps with TensorFlow Lite and ML Kit -- Building the purrfect cat locator app with TensorFlow Object Detection API -- Becoming a maker: exploring embedded AI at the edge -- Simulating a self-driving car using end-to-end deep learning with Keras -- Building an autonomous car in under an hour: reinforcement learning with AWS DeepRacer | |
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Datensatz im Suchindex
| _version_ | 1823924580295639040 |
|---|---|
| adam_text | |
| any_adam_object | |
| author | Koul, Anirudh Ganju, Siddha Kasam, Meher |
| author_facet | Koul, Anirudh Ganju, Siddha Kasam, Meher |
| author_role | aut aut aut |
| author_sort | Koul, Anirudh |
| author_variant | a k ak s g sg m k mk |
| building | Verbundindex |
| bvnumber | BV046259573 |
| classification_rvk | ST 250 ST 300 |
| collection | ZDB-30-PQE |
| contents | Exploring the landscape of Artificial Intelligence -- What's in the picture: image classification with Keras -- Cats versus dogs: transfer learning in 30 lines with Keras -- Building a reverse image search engine: understanding embeddings -- From novice to master predictor: maximizing convolutional neural network accurcy -- Maximizing speed and performance of TensorFlow: a handy checklist -- Practical tools, tips, and tricks -- Cloud APIs for computer vision: up and running in 15 minutes -- Scalable inference serving on Cloud with TensorFlow Serving and KubeFlow -- AI in the browser with TensorFlow.js and mI5.js -- Real-time object classification on iOS with Core ML -- Not hotdog on iOS with Core ML and Create ML -- Shazam for food: developing android apps with TensorFlow Lite and ML Kit -- Building the purrfect cat locator app with TensorFlow Object Detection API -- Becoming a maker: exploring embedded AI at the edge -- Simulating a self-driving car using end-to-end deep learning with Keras -- Building an autonomous car in under an hour: reinforcement learning with AWS DeepRacer |
| ctrlnum | (OCoLC)1128856236 (DE-599)BVBBV046259573 |
| discipline | Informatik |
| edition | First edition |
| format | Electronic eBook |
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| id | DE-604.BV046259573 |
| illustrated | Not Illustrated |
| indexdate | 2025-02-13T07:00:26Z |
| institution | BVB |
| isbn | 9781492034810 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031637610 |
| oclc_num | 1128856236 |
| open_access_boolean | |
| owner | DE-1050 DE-523 |
| owner_facet | DE-1050 DE-523 |
| physical | 1 Online-Ressource (viii, 585 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE FHD01_PQE_Kauf |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | O'Reilly |
| record_format | marc |
| spelling | Koul, Anirudh Verfasser aut Practical deep learning for cloud, mobile, and edge real-world AI and computer vision projects using Python, Keras and TensorFlow Anirudh Koul, Siddha Ganju, and Meher Kasam Real-world AI and computer-vision projects using Python, Keras, and TensorFlow First edition Beijing O'Reilly 2019 1 Online-Ressource (viii, 585 Seiten) txt rdacontent c rdamedia cr rdacarrier Includes index Exploring the landscape of Artificial Intelligence -- What's in the picture: image classification with Keras -- Cats versus dogs: transfer learning in 30 lines with Keras -- Building a reverse image search engine: understanding embeddings -- From novice to master predictor: maximizing convolutional neural network accurcy -- Maximizing speed and performance of TensorFlow: a handy checklist -- Practical tools, tips, and tricks -- Cloud APIs for computer vision: up and running in 15 minutes -- Scalable inference serving on Cloud with TensorFlow Serving and KubeFlow -- AI in the browser with TensorFlow.js and mI5.js -- Real-time object classification on iOS with Core ML -- Not hotdog on iOS with Core ML and Create ML -- Shazam for food: developing android apps with TensorFlow Lite and ML Kit -- Building the purrfect cat locator app with TensorFlow Object Detection API -- Becoming a maker: exploring embedded AI at the edge -- Simulating a self-driving car using end-to-end deep learning with Keras -- Building an autonomous car in under an hour: reinforcement learning with AWS DeepRacer Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Keras Framework, Informatik (DE-588)1160521077 gnd rswk-swf Deep Learning (DE-588)1135597375 gnd rswk-swf Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf TensorFlow (DE-588)1153577011 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Artificial intelligence Application software Maschinelles Lernen (DE-588)4193754-5 s Deep Learning (DE-588)1135597375 s Keras Framework, Informatik (DE-588)1160521077 s TensorFlow (DE-588)1153577011 s Künstliche Intelligenz (DE-588)4033447-8 s Python Programmiersprache (DE-588)4434275-5 s 1\p DE-604 Ganju, Siddha Verfasser aut Kasam, Meher Verfasser aut Erscheint auch als Online-Ausgabe 978-1-492-03479-7 Erscheint auch als Druck-Ausgabe 978-1-492-03486-5 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Koul, Anirudh Ganju, Siddha Kasam, Meher Practical deep learning for cloud, mobile, and edge real-world AI and computer vision projects using Python, Keras and TensorFlow Exploring the landscape of Artificial Intelligence -- What's in the picture: image classification with Keras -- Cats versus dogs: transfer learning in 30 lines with Keras -- Building a reverse image search engine: understanding embeddings -- From novice to master predictor: maximizing convolutional neural network accurcy -- Maximizing speed and performance of TensorFlow: a handy checklist -- Practical tools, tips, and tricks -- Cloud APIs for computer vision: up and running in 15 minutes -- Scalable inference serving on Cloud with TensorFlow Serving and KubeFlow -- AI in the browser with TensorFlow.js and mI5.js -- Real-time object classification on iOS with Core ML -- Not hotdog on iOS with Core ML and Create ML -- Shazam for food: developing android apps with TensorFlow Lite and ML Kit -- Building the purrfect cat locator app with TensorFlow Object Detection API -- Becoming a maker: exploring embedded AI at the edge -- Simulating a self-driving car using end-to-end deep learning with Keras -- Building an autonomous car in under an hour: reinforcement learning with AWS DeepRacer Künstliche Intelligenz (DE-588)4033447-8 gnd Keras Framework, Informatik (DE-588)1160521077 gnd Deep Learning (DE-588)1135597375 gnd Python Programmiersprache (DE-588)4434275-5 gnd TensorFlow (DE-588)1153577011 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)1160521077 (DE-588)1135597375 (DE-588)4434275-5 (DE-588)1153577011 (DE-588)4193754-5 |
| title | Practical deep learning for cloud, mobile, and edge real-world AI and computer vision projects using Python, Keras and TensorFlow |
| title_alt | Real-world AI and computer-vision projects using Python, Keras, and TensorFlow |
| title_auth | Practical deep learning for cloud, mobile, and edge real-world AI and computer vision projects using Python, Keras and TensorFlow |
| title_exact_search | Practical deep learning for cloud, mobile, and edge real-world AI and computer vision projects using Python, Keras and TensorFlow |
| title_full | Practical deep learning for cloud, mobile, and edge real-world AI and computer vision projects using Python, Keras and TensorFlow Anirudh Koul, Siddha Ganju, and Meher Kasam |
| title_fullStr | Practical deep learning for cloud, mobile, and edge real-world AI and computer vision projects using Python, Keras and TensorFlow Anirudh Koul, Siddha Ganju, and Meher Kasam |
| title_full_unstemmed | Practical deep learning for cloud, mobile, and edge real-world AI and computer vision projects using Python, Keras and TensorFlow Anirudh Koul, Siddha Ganju, and Meher Kasam |
| title_short | Practical deep learning for cloud, mobile, and edge |
| title_sort | practical deep learning for cloud mobile and edge real world ai and computer vision projects using python keras and tensorflow |
| title_sub | real-world AI and computer vision projects using Python, Keras and TensorFlow |
| topic | Künstliche Intelligenz (DE-588)4033447-8 gnd Keras Framework, Informatik (DE-588)1160521077 gnd Deep Learning (DE-588)1135597375 gnd Python Programmiersprache (DE-588)4434275-5 gnd TensorFlow (DE-588)1153577011 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Künstliche Intelligenz Keras Framework, Informatik Deep Learning Python Programmiersprache TensorFlow Maschinelles Lernen |
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