January 2019
Intermediate to advanced
490 pages
15h 37m
English
Content preview from Serverless Programming Cookbook
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How to do it...
In this recipe, we will learn how to make predictions with an AWS ML service for binary classification using AWS CLI by going through the following steps:
- Prepare the data as a CSV and upload it to S3. Amazon ML requires a CSV with each row corresponding to an observation that may be used for training or testing. Each column also needs a name, which you can specify as the first row or specify separately using a schema file. You may also split data into multiple CSV files within the same bucket. If you have multiple files, you should provide a path ending with a forward slash (/).
As mentioned in the Getting ready section, we will reuse the sample data available in AWS, which is already uploaded to S3 at s3://aml-sample-data/banking.csv ...
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