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Updated in [May 30th, 2023]
What does this course tell?
(Please note that the following overview content is from the original platform)
- Welcome.
- Learning objectives.
- What is regression?.
- The plan: Predicting bike rentals.
- Knowledge Check.
- Feature Engineering with recipes.
- Resampling for evaluating model performance.
- Summary and conclusion
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We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
Welcome to Learn Live - Introduction to regression models by using R and tidymodels! In this course, you will learn the basics of regression models and how to use R and tidymodels to build and evaluate them.
Regression models are powerful tools for predicting outcomes based on a set of input variables. In this course, you will learn how to use R and tidymodels to build and evaluate regression models. You will also learn how to use feature engineering and resampling techniques to improve the performance of your models.
By the end of this course, you will have a better understanding of regression models and how to use them to make predictions. You will also have the skills to apply these techniques to your own projects.
This course is a great starting point for anyone interested in data science and machine learning. It can also be a great way to gain experience in using R and tidymodels for regression models. After completing this course, you can continue to explore more advanced topics in data science and machine learning, such as deep learning and natural language processing. You can also use the skills you learn here to develop your own projects.
