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Crash Course: Machine Learning Pipeline and API using R

person icon Moritz Müller-Navarra

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

updated on icon Updated on Sep, 2023

language icon Language - English

person icon Moritz Müller-Navarra

architecture icon Development,Data Science,Machine Learning

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Course 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

Goals

What will you learn in this course:

  • 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

Prerequisites

What are the prerequisites for this course?

  • R programming
  • Basic Machine Learning knowledge
  • tidyverse
Crash Course: Machine Learning Pipeline and API using R

Curriculum

Check out the detailed breakdown of what’s inside the course

Setup
3 Lectures
  • play icon Introduction 02:30 02:30
  • play icon Installation of R 00:39 00:39
  • play icon Setup 01:41 01:41
Machine Learning - tidymodels
15 Lectures
Tutorialspoint
Building the pipeline
10 Lectures
Tutorialspoint
Outro
1 Lectures
Tutorialspoint

Instructor Details

Moritz Müller-Navarra

Moritz Müller-Navarra

I am an engineer (equiv. Master's degree in engineering & economics) with strong programming skills in R and insights into machine learning. I have published R packages and R shiny applications, currently seeking to acquire new challenging opportunities in data science/analytics while working as a freelancer online. I have expertise in realizing complex projects in R, including machine learning and working on time series analysis. I visit international conferences on R and published two online course on programming and teaching R. I see myself as data scientist/analyst who is continuously improving his skills and likes to work on problems to generate insights for real world applications. In my most recent project I was coaching R programming for the German Federal Statistical Office.

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