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Hands-On Artificial Intelligence on Amazon Web Services
book

Hands-On Artificial Intelligence on Amazon Web Services

by Subhashini Tripuraneni, Charles Song
October 2019
Intermediate to advanced content levelIntermediate to advanced
426 pages
10h 8m
English
Packt Publishing
Content preview from Hands-On Artificial Intelligence on Amazon Web Services

Exploring data

Amazon SageMaker offers built-in tools and capabilities for creating machine learning pipelines that incorporate feedback loops. Since machine learning pipelines were covered in Chapter 8, Creating Machine Learning Inference Pipelines, here, we will focus on the significance of incorporating a feedback loop. Let's begin:

  1. Install the relevant Python packages and set the locations for the training, validation, and model outputs on the S3 bucket, as follows:
!pip install pyarrow!pip install joblib!pip install xgboost#Read the dataset from S3 buckets3_bucket = 'ai-in-aws's3_prefix = 'Click-Fraud's3_train_prefix = os.path.join(s3_prefix, 'train')s3_val_prefix = os.path.join(s3_prefix, 'val')s3_output_prefix = os.path.join(s3_prefix, ...
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Publisher Resources

ISBN: 9781789534146Supplemental Content