From the course: Learning Amazon SageMaker (2019)

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Download and import data

Download and import data

From the course: Learning Amazon SageMaker (2019)

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Download and import data

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- [Instructor] Data analysis process. There are three main steps we'll walk through when looking at this churn dataset example. The first step will be downloading the data from the public web, the second step will be importing the data and we'll use the pandas Python library for that and the third step will be investigating the data. So, on the Notebook Instances screen, open up the Notebook instance that was created earlier by clicking on Open Jupyter Notebook and that will take you to the directory structure that was copied over from the GitHub repository earlier. If you could click on introduction_to_applying_machine_learning and then xgboost_customer_churn. From here open up the xgboost_customer_churn notebook. So, this is a tutorial that's been provided for Amazon SageMaker that goes through how do you train a model using XGBoost and then how to deploy that within the SageMaker environment. I thought this would be a good example to run through as we can do a bit of customization…

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