You're reading from Machine Learning with Amazon SageMaker Cookbook 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments

Product type Paperback

Published in Oct 2021

Publisher Packt

ISBN-13 9781800567030

Length 762 pages

Edition 1st Edition

Languages

Python

Tools

AWS

Concepts

Machine Learning

Author (1):

Joshua Arvin Lat

View More author details

Table of Contents (11) Chapters

Preface

1. Chapter 1: Getting Started with Machine Learning Using Amazon SageMaker

2. Chapter 2: Building and Using Your Own Algorithm Container Image FREE CHAPTER

3. Chapter 3: Using Machine Learning and Deep Learning Frameworks with Amazon SageMaker

4. Chapter 4: Preparing, Processing, and Analyzing the Data

5. Chapter 5: Effectively Managing Machine Learning Experiments

6. Chapter 6: Automated Machine Learning in Amazon SageMaker

7. Chapter 7: Working with SageMaker Feature Store, SageMaker Clarify, and SageMaker Model Monitor

8. Chapter 8: Solving NLP, Image Classification, and Time-Series Forecasting Problems with Built-in Algorithms

9. Chapter 9: Managing Machine Learning Workflows and Deployments

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Generating a synthetic dataset for anomaly detection experiments

In this recipe, we will generate a synthetic dataset that contains outliers or anomalies. This will enable us to perform anomaly detection experiments using algorithms such as the Random Cut Forest (RCF). If this is your first time hearing about anomaly detection, it is the identification of outliers or records that differ significantly from the rest of the records of the dataset. What's the RCF algorithm? The RCF algorithm is an unsupervised algorithm used for detecting these anomalies in the dataset.

After we have generated the synthetic dataset in this recipe, we will use the generated dataset to train and deploy an RCF model and trigger this model within an Amazon Athena query in the Invoking machine learning models with Amazon Athena using SQL queries recipe. This will enable us to tag anomalies in our dataset during the data preparation and analysis phase.

Tip

Since we will show the steps on how to...