- Lab
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Libraries: If you want this lab, consider one of these libraries.
- AI
Evaluating ML Model Performance
In this lab, you’ll practice comparing and evaluating different machine learning model families, logistic regression, decision trees, and neural networks, using PyTorch and scikit-learn. When you’re finished, you’ll have a complete workflow for training, testing, and selecting the best model for deployment.
Lab Info
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.