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Exploring Supervised Learning

Explore the fundamentals of supervised learning with this comprehensive lab. Through detailed steps and hands-on activities, you'll gain practical experience in implementing both regression and classification models. You'll learn how to preprocess and clean data, build and train models using Python, and evaluate model performance using appropriate metrics. This lab will provide you with a solid foundation in supervised learning, essential for solving real-world machine learning problems.

Labs

Path Info

Level
Clock icon Intermediate
Duration
Clock icon 25m
Published
Clock icon Oct 09, 2024

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Table of Contents

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.

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.