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Load a TensorFlow Dataset with Web Data

In this lab, you will practice retrieving data from the internet using Python. Once downloaded, you will parse it and load it into a TensorFlow Dataset. ### Prerequisites This lab is designed to be completed in PyCharm running on your machine. You should have PyCharm and TensorFlow installed before attempting this lab. We will not be covering this setup in the lab.


Path Info

Clock icon Intermediate
Clock icon 30m
Clock icon Aug 13, 2021

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Table of Contents

  1. Challenge

    Retrieve Iris Data from the Internet

    Download the iris data from the UC Irvine Machine Learning Repository.

    Your code should be respectful of their bandwidth and not repeatedly download the data once it is available locally.

  2. Challenge

    Prepare the Iris Data

    Load the iris data into your program. Convert the raw data to appropriate types for training a model.

  3. Challenge

    Load the Data into a TensorFlow Dataset

    Split the data into features and labels. Create a Dataset from the features and labels.

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