This is the code repository for Time Series Analysis on AWS, published by Packt.
Learn how to build forecasting models and detect anomalies in your time series data
Being a business analyst and data scientist, you have to use many algorithms and approaches to prepare, process, and build ML-based applications by leveraging time series data, but you face common problems, such as not knowing which algorithm to choose or how to combine and interpret them. Amazon Web Services (AWS) provides numerous services to help you build applications fueled by artificial intelligence (AI) capabilities. This book helps you get to grips with three AWS AI/ML-managed services to enable you to deliver your desired business outcomes.
This book covers the following exciting features: <First 5 What you'll learn points>
- Understand how time series data differs from other types of data
- Explore the key challenges that can be solved using time series data
- Forecast future values of business metrics using Amazon Forecast
- Detect anomalies and deliver forewarnings using Lookout for Equipment
- Detect anomalies in business metrics using Amazon Lookout for Metrics
- Visualize your predictions to reduce the time to extract insights
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
START = '2013-06-01'
END = '2013-07-31'
DATASET = 'household_energy_consumption'
FORECAST_PREFIX = 'export_energy_consumption_XXXX'
Following is what you need for this book: If you're a data analyst, business analyst, or data scientist looking to analyze time series data effectively for solving business problems, this is the book for you. Basic statistics knowledge is assumed, but no machine learning knowledge is necessary. Prior experience with time series data and how it relates to various business problems will help you get the most out of this book. This guide will also help machine learning practitioners find new ways to leverage their skills to build effective time series-based applications.
With the following software and hardware list you can run all code files present in the book (Chapter 1-15).
| Chapter | AWS services covered in the book | OS required |
|---|---|---|
| 1 - 15 | Amazon Forecast | Any browser (Chrome recommended) running on Windows, Mac OS X, and Linux (Any) |
| 1 - 15 | Amazon Lookout for Equipment | Any browser (Chrome recommended) running on Windows, Mac OS X, and Linux (Any) |
| 1 - 15 | Amazon Lookout for Metrics | Any browser (Chrome recommended) running on Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Michaël Hoarau is an AI/ML specialist solutions architect (SA) working at Amazon Web Services (AWS). He is an AWS Certified Associate SA. He previously worked as an AI/ML specialist SA at AWS and the EMEA head of data science at GE Digital. He has experience in building product quality prediction systems for multiple industries. He has used forecasting techniques to build virtual sensors for industrial production lines. He has also helped multiple customers build forecasting and anomaly detection systems to increase their business efficiency.
If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.