Offered By: IBMSkillsNetwork

Learn to automate feature selection with lasso regression

Join this project to learn feature automation with Lasso Regression using Sklearn in Python. Optimize model performance using regularization techniques and hyperparameter tuning with different Python libraries. Explore why this technique is crucial for feature selection through the creation of insightful data visualizations. Join us to gain practical experience with Lasso Regression – a powerful tool for optimizing models and elevating predictive performance.

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Guided Project

Machine Learning

105 Enrolled
4.8
(13 Reviews)

At a Glance

Join this project to learn feature automation with Lasso Regression using Sklearn in Python. Optimize model performance using regularization techniques and hyperparameter tuning with different Python libraries. Explore why this technique is crucial for feature selection through the creation of insightful data visualizations. Join us to gain practical experience with Lasso Regression – a powerful tool for optimizing models and elevating predictive performance.

Explore the power of Lasso Regression in this project, where we learn its necessity, applications, and significance in the realm of machine learning. Discover why Lasso Regression is essential for feature selection by producing different data visualizations. Join us to gain hands-on experience with Lasso Regression, a valuable tool in optimizing models and enhancing predictive performance.

This hands-on project is based on the Apply lasso regression to automate feature selection tutorial. This Guided Project format combines the instructions of the tutorial with the environment to execute these instructions without the need to download, install, and configure tools.
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A Look at the Project Ahead

While completing this project, you will:
  • Gain a solid understanding of regularization concepts in the context of linear regression models.
  • Learn to load and manipulate datasets using essential libraries such as NumPy and Pandas
  • Implement Lasso Regression for linear models using Sklearn and leverage grid search for hyperparameter tuning

What You'll Need

  • No Installation Required: Everything will be available in the JupyterLab including any Python libraries and data sets
  • Basic Understanding of Python: This project is beginner-friendly, but having a basic understanding of Python will make it easier.
  • Basic Understanding of Statistical Concepts: A basic understanding of statistic concepts will be beneficial but not required. This tutorial starts off by explaining lasso regression to guide you throughout the project.

Certificate

No Certificate Offered

Estimated Effort

30 Minutes

Level

Beginner

Industries

Skills You Will Learn

Artificial Intelligence, Machine Learning, Numpy, Pandas, Python, sklearn

Language

English

Course Code

GPXX0E0MEN

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