Crash Course: Machine Learning Pipeline and API using R

Crash Course: Machine Learning Pipeline and API using R, available at $54.99, has an average rating of 4.25, with 24 lectures, 7 quizzes, based on 6 reviews, and has 46 subscribers.

You will learn about 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 This course is ideal for individuals who are You want to learn tidymodels or You want to build a regression model using R or You need a quick and dense introduction into pipelines It is particularly useful for You want to learn tidymodels or You want to build a regression model using R or You need a quick and dense introduction into pipelines.

Enroll now: Crash Course: Machine Learning Pipeline and API using R

Summary

Title: Crash Course: Machine Learning Pipeline and API using R

Price: $54.99

Average Rating: 4.25

Number of Lectures: 24

Number of Quizzes: 7

Number of Published Lectures: 24

Number of Published Quizzes: 7

Number of Curriculum Items: 31

Number of Published Curriculum Objects: 31

Original Price: $24.99

Quality Status: approved

Status: Live

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

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

Target Audiences

You want to learn tidymodels
You want to build a regression model using R
You need a quick and dense introduction into pipelines

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

Course Curriculum

Chapter 1: Setup

Lecture 1: Introduction

Lecture 2: Installation of R & RStudio

Lecture 3: Setup

Lecture 4: Install Packages

Chapter 2: tidymodels & workflowsets

Lecture 1: Splitting data – rsample

Lecture 2: Preprocess data – recipes I

Lecture 3: Preprocess data – recipes II

Lecture 4: Train models – parsnip

Lecture 5: Tune hyperparameters – tune

Lecture 6: Tune hyperparameters – tune II

Lecture 7: Preprocess and tune – workflows

Lecture 8: Multiple workflows – workflowsets I

Lecture 9: Multiple workflows – workflowsets II

Chapter 3: Building the pipeline

Lecture 1: Intro

Lecture 2: plumber

Lecture 3: Pipeline – Basics

Lecture 4: Pipeline – Steps I

Lecture 5: Pipeline – Steps II

Lecture 6: Pipeline – predict endpoint

Lecture 7: Pipeline – report endpoint

Lecture 8: Pipeline – Interaction

Lecture 9: Pipeline – Adding a new preprocessor

Lecture 10: Pipeline – Adding a new model

Chapter 4: Outro

Lecture 1: Thank you

Instructors

Moritz Müller-Navarra
Data Scientist (Freelancer)

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 2 votes
4 stars: 1 votes
5 stars: 3 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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