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Hands-On Artificial Intelligence on Amazon Web Services

You're reading from   Hands-On Artificial Intelligence on Amazon Web Services Decrease the time to market for AI and ML applications with the power of AWS

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Product type Paperback
Published in Oct 2019
Publisher Packt
ISBN-13 9781789534146
Length 426 pages
Edition 1st Edition
Tools
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Authors (2):
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Subhashini Tripuraneni Subhashini Tripuraneni
Author Profile Icon Subhashini Tripuraneni
Subhashini Tripuraneni
Charles Song Charles Song
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Charles Song
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Introduction and Anatomy of a Modern AI Application FREE CHAPTER
2. Introduction to Artificial Intelligence on Amazon Web Services 3. Anatomy of a Modern AI Application 4. Section 2: Building Applications with AWS AI Services
5. Detecting and Translating Text with Amazon Rekognition and Translate 6. Performing Speech-to-Text and Vice Versa with Amazon Transcribe and Polly 7. Extracting Information from Text with Amazon Comprehend 8. Building a Voice Chatbot with Amazon Lex 9. Section 3: Training Machine Learning Models with Amazon SageMaker
10. Working with Amazon SageMaker 11. Creating Machine Learning Inference Pipelines 12. Discovering Topics in Text Collection 13. Classifying Images Using Amazon SageMaker 14. Sales Forecasting with Deep Learning and Auto Regression 15. Section 4: Machine Learning Model Monitoring and Governance
16. Model Accuracy Degradation and Feedback Loops 17. What Is Next? 18. Other Books You May Enjoy

Understanding model sales through DeepAR

As noted in the introduction to this chapter, managing inventory for retailers is a complex activity to handle. Holidays, special events, and markdowns can have a significant impact on how a store performs and, in turn, how a department within a store performs.

The Kaggle dataset contains historical sales for 45 stores, with each store belonging to a specific type (location and performance) and size. The retailer runs several promotional markdowns throughout the year. These markdowns precede holidays, such as SuperBowl, Labor Day, Thanksgiving, and Christmas.

Brief description of the dataset

Let's briefly consider the dataset that we are about to model:

  • Features data: This is...
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