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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide - Second Edition

You're reading from  AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide - Second Edition

Product type Book
Published in Feb 2024
Publisher Packt
ISBN-13 9781835082201
Pages 342 pages
Edition 2nd Edition
Languages
Authors (2):
Somanath Nanda Somanath Nanda
Profile icon Somanath Nanda
Weslley Moura Weslley Moura
Profile icon Weslley Moura
View More author details

Table of Contents (13) Chapters

Preface 1. Chapter 1: Machine Learning Fundamentals 2. Chapter 2: AWS Services for Data Storage 3. Chapter 3: AWS Services for Data Migration and Processing 4. Chapter 4: Data Preparation and Transformation 5. Chapter 5: Data Understanding and Visualization 6. Chapter 6: Applying Machine Learning Algorithms 7. Chapter 7: Evaluating and Optimizing Models 8. Chapter 8: AWS Application Services for AI/ML 9. Chapter 9: Amazon SageMaker Modeling 10. Chapter 10: Model Deployment 11. Chapter 11: Accessing the Online Practice Resources 12. Other Books You May Enjoy

Storing the training data

First of all, you can use multiple AWS services to prepare data for machine learning, such as Elastic MapReduce (EMR), Redshift, Glue, and so on. After preprocessing the training data, you should store it in S3, in a format expected by the algorithm you are using. Table 6.1 shows the list of acceptable data formats per algorithm.

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Data format

Algorithm

Application/x-image

Object detection algorithm, semantic segmentation

Application/x-recordio

Object detection algorithm

Application/x-recordio-protobuf

Factorization machines, K-Means, KNN, latent Dirichlet allocation, linear learner, NTM, PCA, RCF, sequence-to-sequence

Application/jsonlines

BlazingText, DeepAR