In this course, you will begin by gaining a comprehensive understanding of linear regression, ridge regression, and lasso regression. These foundational concepts in machine learning are essential for anyone interested in data analysis and predictive modeling. You will learn how these models work and how they manipulate datasets to establish a correlation between independent variables and the dependent variable. This understanding will enable you to forecast outcomes based on the input data effectively.

As you progress, you will have the opportunity to implement both ridge and lasso regression models within your Google Colab project. This hands-on experience will allow you to apply theoretical knowledge in a practical setting, enhancing your learning process and boosting your confidence in using these models. After implementing the models, you will evaluate their performance by scoring them and comparing the results. This comparison will help you determine which model performs better in predicting outcomes based on your dataset.

By the end of this course, you should have a solid foundation in regression machine learning models. You will be equipped with the skills necessary to apply these techniques in real-life scenarios, empowering you to make informed data-driven decisions and insights in various contexts. Furthermore, applying these models to real-life scenarios will give you a great insight on recent data-analytics jobs.

このコースの対象受講者:

• Beginners with interest in machine learning