Create machine learning models with R and tidymodels
- Offered byMicrosoft
Create machine learning models with R and tidymodels at Microsoft Overview
Duration | 5 hours |
Total fee | Free |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Create machine learning models with R and tidymodels at Microsoft Course details
- Explore and analyze data with R
- Introduction to regression models by using R and tidymodels
- Introduction to classification models by using R and tidymodels
- Introduction to clustering models by using R and tidymodels
- Learn how to explore and analyze data by using R
- Get an introduction to regression models, classification models, and clustering models by using tidymodels and R
- In this learning path, you'll learn common data exploration and analysis tasks
- In this course, you'll explore, analyze, and visualize data by using the R programming language
- In machine learning, the goal of regression is to create a model that can predict a numeric, quantifiable value
- In this course, you learn how to use the R programming language and tidymodels framework to train classification models
Create machine learning models with R and tidymodels at Microsoft Curriculum
Explore and analyze data with R
Introduction
Exploratory data analysis
Exercise - Transform data by using dplyr
Visualize your data
Exercise - Visualize your data by using ggplot2
Examine real-world data
Exercise - Examine real-world data
Knowledge check
Challenge - Data exploration
Summary
Introduction to regression models by using R and tidymodels
Introduction
What is regression?
Exercise - Train and evaluate a regression model
Discover new regression models
Exercise - Experiment with more powerful regression models
Improve models with hyperparameters
Exercise - Optimize and save models
Knowledge check
Challenge - Regression
Summary
Introduction to classification models by using R and tidymodels
Introduction
What is classification?
Exercise - Train and evaluate a binary classification model
Evaluate classification models
Exercise - Train a classification model by using alternative metrics
Create multiclass classification models
Exercise - Train and evaluate multiclass classification models
Knowledge check
Challenge - Train a classification model to classify wine data
Summary
Introduction to clustering models by using R and tidymodels
Introduction
What is clustering?
Exercise - Train and evaluate a clustering model
Evaluate different types of clustering
Exercise - Train and evaluate advanced clustering models
Knowledge check
Challenge - Clustering
Summary
Create machine learning models with R and tidymodels at Microsoft Entry Requirements
- Knowledge of basic mathematicsSome experience programming in R
- Not mentioned
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