Model Parameters and Hyperparameters Overview
Model Parameters and Hyperparameters Overview Data Science Project
Introduction to Supervised Learning with scikit-learn

Model Parameters and Hyperparameters Overview

In this lab, we'll explore these concepts using various machine learning models and their associated hyperparameters.
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Model Parameters and Hyperparameters OverviewModel Parameters and Hyperparameters Overview
Project Created by

Verónica Barraza

Project Activities

All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.

All our activities include solutions with explanations on how they work and why we chose them.

multiplechoice

Which of the following is NOT a machine learning model used in the exercise?

multiplechoice

How can changing hyperparameter values impact a model's performance?

multiplechoice

True or False: The accuracy of the SVM with linear kernel model decreases with low values of C.

multiplechoice

True or False: The accuracy of the Random Forest model decreases with low values of max_depth (with max_depth=2 and 5).

Model Parameters and Hyperparameters OverviewModel Parameters and Hyperparameters Overview
Project Created by

Verónica Barraza

This project is part of

Introduction to Supervised Learning with scikit-learn

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