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Linear Regression Performed Using Amazon SageMaker

Imagine you are the data engineer at your company and your company just selected AWS as the preferred cloud provider. You have been asked to train an ML model using linear learner algorithm. In this lab, you will fetch the iris data and use that as the input dataset. Once the data is split, the data is uploaded to S3 bucket. Then the Sagemaker estimator is configured before initiating the training process.

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Path Info

Level
Clock icon Intermediate
Duration
Clock icon 1h 0m
Published
Clock icon Apr 12, 2024

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Table of Contents

  1. Challenge

    Launch SageMaker Notebook

    1. Log in to the AWS console and navigate to AWS SageMaker.
    2. Load the Jupyter Notebook that has been provided with this hands-on lab.

  2. Challenge

    Install dependencies and import the libraries

    1. Load required libraries.
    2. Fetch the dataset from sklearn library.

  3. Challenge

    Download the data and upload them to S3 bucket

    1. Convert the downloaded data to a CSV format
    2. Use the upload_file function and upload the CSV files to S3 bucket

  4. Challenge

    Set up training and validation data

    1. Create the inputs for the fit() function with the training and validation location.

  5. Challenge

    Train the model

    1. Fetch the linear learner image according to the region.
    2. Setup the estimator function.
    3. initiate the training process using the fit() function.
A Cloud Guru - Labs - Linear Regression Performed Using Amazon SageMaker
Author
A Cloud Guru

The Cloud Content team comprises subject matter experts hyper focused on services offered by the leading cloud vendors (AWS, GCP, and Azure), as well as cloud-related technologies such as Linux and DevOps. The team is thrilled to share their knowledge to help you build modern tech solutions from the ground up, secure and optimize your environments, and so much more!

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