Creating a scikit-learn Random Forest Classifier in Amazon SageMaker

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Creating a scikit-learn Random Forest Classifier in Amazon SageMaker

Scikit-learn is a great place to start working with machine learning. In this lab, we will use scikit-learn to create a Random Forest Classifier to determine if you prefer cats or dogs. The data set being used is entirely made up, but could easily be swapped with one of your own!

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Lab Info

Level

Advanced

Last updated

Sep 22, 2025

Duration

1h 0m

Challenge

Navigate to the Jupyter Notebook

Log in to the AWS console and navigate to the AWS SageMaker page. From there, load the Jupyter Notebook that has been provided with this hands-on lab.
Challenge

Load and Prepare the Data
1. Load the survey data from data.csv, located beside the notebook.
2. View the data. Look at both the raw data and statistics for the data.
3. Change the column data types so the model can understand them.
4. Split the data into training and testing sets. Use 80% of the data for training.
Challenge

Train the Random Forest Model
1. Create a Random Forest Classifier model using scikit-learn.
2. Train the model using the training data.
Challenge

Evaluate the Model
1. Generate predictions for the testing data set.
2. View the confusion matrix for the predictions.
3. Calculate the sensitivity and specificity.
4. Plot the ROC curve.
5. Calculate the area under the curve.
Challenge

Predict for Yourself
1. Create a survey response for yourself.
2. Have the model predict if you prefer cats or dogs.

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