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|a C4C0C653-AFDA-4036-8850-7B1DD0B553E4
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|n http://www.overdrive.com
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|a Q325.5
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|a HCDD
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1 |
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|a Tripuraneni, Subhashini,
|e author
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| 245 |
1 |
0 |
|a Hands-on artificial intelligence on Amazon Web Services :
|b decrease the time to market for AI and ML applications with the power of AWS /
|c Subhashini Tripuraneni ; Charles Song
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| 264 |
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1 |
|a Birmingham :
|b Packt Publishing, Limited,
|c 2019
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| 300 |
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|a 1 online resource (vi, 412 pages) :
|b black and white illustrations
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a unmediated
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|2 rdamedia
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| 338 |
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|a volume
|b nc
|2 rdacarrier
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| 520 |
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|a AI in AWS covers primarily two broad topics - a) how to leverage readily available AI/ML APIs and b) how to build, train and deploy ML models from scratch, to solve diverse business problems, such as demand forecasting, image classification, topic modeling, speech and text recognition.
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| 505 |
0 |
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|a Section 1: Introduction and anatomy of a modern AI -- Chapter 1: Introduction to artificial intelligence on Amazon Web Services -- Chapter 2: Anatomy of a modern AI application -- Section 2: Building applications with AWS AI -- Chapter 3: Detecting and translating text with Amazon Rekognition -- Chapter 4: Performing speech-to-text and vice versa with Amazon transcribe and Polly -- Chapter 5: Extracting information from text with Amazon comprehend -- Chapter 6: Building a voice chatbot with Amazon Lex -- Section 3: Training machine learning models with Amazon SageMaker -- Chapter 7: Working with Amazon Sagemaker -- Chapter 8 : Creating machine learning inference pipelines -- Chapter 9 : Discovering topics in text collection -- Chapter 10: Classifying images using Amazon Sagemaker -- Chapter 11: Sales forecasting with Deep Learning and Auto Regression -- Section 4: Machine learning model monitoring and governance -- Chapter 12: Model accuracy degradation and feedback loops.
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|a Amazon Web Services (Firm)
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| 610 |
2 |
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|a Amazon Web Services (Firm)
|2 fast
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0 |
|a Machine learning.
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| 650 |
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7 |
|a Distributed systems.
|2 bicssc
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| 650 |
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7 |
|a Mathematical theory of computation.
|2 bicssc
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| 650 |
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7 |
|a Machine learning.
|2 bicssc
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| 650 |
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7 |
|a Artificial intelligence.
|2 bicssc
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| 650 |
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7 |
|a Computers
|x Machine Theory.
|2 bisacsh
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| 650 |
|
7 |
|a Computers
|x Systems Architecture
|x Distributed Systems & Computing.
|2 bisacsh
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| 650 |
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7 |
|a Computers
|x Intelligence (AI) & Semantics.
|2 bisacsh
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| 650 |
|
7 |
|a Machine learning
|2 fast
|
| 700 |
1 |
|
|a Song, Charles,
|e author
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| 758 |
|
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|i has work:
|a Hands-On Artificial Intelligence on Amazon Web Services (Work)
|1 https://id.oclc.org/worldcat/entity/E39PD3PHrfqRhjY4wqp7hMkJQm
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Tripuraneni, Subhashini.
|t Hands-On Artificial Intelligence on Amazon Web Services : Decrease the Time to Market for AI and ML Applications with the Power of AWS.
|d Birmingham : Packt Publishing, Limited, ©2019
|z 9781789534146
|
| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=5928313
|y Click for online access
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| 903 |
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|a EBC-AC
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