- Lab
- A Cloud Guru
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
Table of Contents
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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.
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Challenge
Prepare the Iris Data
Load the iris data into your program. Convert the raw data to appropriate types for training a model.
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Challenge
Load the Data into a TensorFlow Dataset
Split the data into features and labels. Create a Dataset from the features and labels.
What's a lab?
Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.
Provided environment for hands-on practice
We will provide the credentials and environment necessary for you to practice right within your browser.
Guided walkthrough
Follow along with the author’s guided walkthrough and build something new in your provided environment!
Did you know?
On average, you retain 75% more of your learning if you get time for practice.
