- Lab
- Cloud
Using Amazon S3 as a Machine Learning Repository
Imagine you are a starting Data Engineer. You have been tasked with preparing an environment for model building. In order to complete this task you need to ingest a csv file into S3 and then load that data source into a Jupyter Notebook. Finally you need to save that data back into S3 under a different table.
Path Info
Table of Contents
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Challenge
Prepare the Environment
Create a Jupyter Notebook in SageMaker AI, and an S3 bucket with a CSV file. (See the Project Guide or videos for specific commands, and any URLs.)
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Challenge
Ingest Data Into SageMaker
Ingest data from the S3 bucket's fiile into the Jupyter Notebook, modify the data, then write the table back to the S3 as a new CSV file.
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