- Lab
-
Libraries: If you want this lab, consider one of these libraries.
- AI
- Cloud
Comparing Machine Learning Algorithms on a Single Dataset using Amazon SageMaker
Imagine you are the data engineer, and you have been assigned the task of finding an optimal ML algorithm by comparing multiple algorithms. This lab will take the California housing dataset and predict the median housing value. In this hands-on lab, you will learn how to train multiple regression algorithms, predict for test data and compare core regression metrics.
Lab Info
Table of Contents
-
Challenge
Launch SageMaker Notebook
- Log in to the AWS console and navigate to AWS SageMaker.
- Load the Jupyter Notebook that has been provided with this hands-on lab.
-
Challenge
Load Libraries and Fetch the Data
- Load required libraries.
- Fetch the dataset from sklearn library.
-
Challenge
Train the Model with Multiple Algorithms
- Create an instance of three algorithms that will be compared.
- Train the algorithms individually.
-
Challenge
Predict and Compare
- Run predictions against test data.
- Compare key metrics of the three algorithms.
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.
Learn by doing
Engage hands-on with the tools and technologies you’re learning. You pick the skill, we provide the credentials and environment.
Follow your guide
All labs have detailed instructions and objectives, guiding you through the learning process and ensuring you understand every step.
Turn time into mastery
On average, you retain 75% more of your learning if you take time to practice. Hands-on labs set you up for success to make those skills stick.