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Applying AI to Image Data

In this hands-on lab, "Applying ML to Image Data," you’ll learn how to preprocess and analyze images for machine learning. Begin by understanding how images are represented as numerical matrices and master essential techniques like resizing and normalization. Build and train convolutional neural networks (CNNs), starting with a simple model and progressing to advanced architectures. Through guided exercises, you’ll visualize how models learn and evaluate performance with metrics like accuracy and loss. By the end, you’ll have the skills to tackle image classification tasks and the confidence to explore advanced computer vision topics. Start your journey today! 🚀

Lab platform
Lab Info
Level
Intermediate
Last updated
Mar 11, 2025
Duration
30m

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About the author

Danny Sullivan is a former special education teacher and professional baseball player that moved into software development in 2014. He’s experienced with Ruby, Python and JavaScript ecosystems, but enjoys Ruby most for its user friendliness and rapid prototyping capabilities.

Real skill practice before real-world application

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.

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Engage hands-on with the tools and technologies you’re learning. You pick the skill, we provide the credentials and environment.

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