Crash Course: Machine Learning Pipeline and API using R
Build a dynamic Machine Learning Pipeline, which you can use in Data Science and Data Analysis Projects
Ratings 4.18 / 5.00
What You Will Learn!
- Build a regression pipeline with R using tidymodels
- Make your analysis available through plumber
- Make predictions on a new data set using your trained model
- Visualize cross validation results
- Learn how to render a rmarkdown document as html with parameters
- Learn how to tune hyperparameters using tidymodels
Description
Hi,
in this course you are going to get a quick introduction into the fascinating world of building predictive models in R using tidymodels. This course guides you through important packages of tidymodels to empower you to build an automatic regression pipeline, which you can use to tune a model for your own data set. I will introduce you to tidymodels and show you how you can build a simple API using plumber.
We discover the important packages together. After each video in the first chapter you will solve short quizzes to deepen your knowledge. Step by step you will learn the important parts to build a regression pipeline.
In the second chapter we will finally build the pipeline, which you can customize to your specific needs. We will make the pipeline available through plumber.
This course is pretty dense in nature, but I believe that it is a very good starting point for you, since you will be able to build upon the material provided to you.
I assume that you are familiar with R, tidyverse principles and the basics of machine learning. But even If you are a complete beginner, I think that this course can be valuable to you.
I am looking forward seeing you in the course,
Sincerely Moritz
Who Should Attend!
- You want to learn tidymodels
- You want to build a regression model using R
- You need a quick and dense introduction into pipelines
