| File Name: | R tidymodels part 3: Classification |
| Content Source: | https://www.udemy.com/course/r-tidymodels-part-3-classification |
| Genre / Category: | Programming |
| File Size : | 6.1 GB |
| Publisher: | Marko Intihar, PhD |
| Updated and Published: | October 25, 2025 |
This course is designed for learners who want to build models that predict categories, not numbers, and who wish to understand the statistical and machine learning foundations behind them.
What You’ll Learn
In this course, you’ll move from probability intuition to full-scale classification workflows using tidymodels, R’s modern ecosystem for machine learning:
- Understand what classification is and how it differs from regression
- Learn the logic of logistic regression and its link to probabilities, odds, and log-odds
- Fit and interpret logistic regression models using maximum likelihood estimation
- Evaluate models with accuracy, precision, recall, specificity, and F1 score
- Visualize model performance through ROC and AUC curves
- Adjust probability thresholds and see their effect on predictions
- Handle imbalanced data using balanced accuracy, threshold tuning, and advanced metrics
- Apply resampling techniques such as upsampling, downsampling, and SMOTE
- Build and tune K-nearest neighbors (KNN) classifiers
- Explore Naive Bayes as a probabilistic classifier for both numeric and text data
- Preprocess text using textrecipes and create a simple spam-filtering model
- Compare multiple classification models within the same tidymodels workflow
Why Take This Course?
Classification problems are everywhere — from medical diagnostics and fraud detection to email filtering and customer segmentation.
This course helps you understand how these models make decisions and how to evaluate them responsibly.
You’ll gain not only the technical skills to build classification models but also the intuition to select the right metric and interpret model behavior — all while keeping your work tidy, reproducible, and explainable.
What You’ll Get:
- Clear, structured explanations of classification theory and practice
- Step-by-step modeling workflows in R and tidymodels
- Real-world examples and visual explanations of metrics
- Exercises and assignments with full solutions
- All code, datasets, and outputs provided
- Lifetime access and updates
DOWNLOAD LINK: R tidymodels part 3: Classification
R_tidymodels_part_3_Classification.part1.rar – 1000.0 MB
R_tidymodels_part_3_Classification.part2.rar – 1000.0 MB
R_tidymodels_part_3_Classification.part3.rar – 1000.0 MB
R_tidymodels_part_3_Classification.part4.rar – 1000.0 MB
R_tidymodels_part_3_Classification.part5.rar – 1000.0 MB
R_tidymodels_part_3_Classification.part6.rar – 1000.0 MB
R_tidymodels_part_3_Classification.part7.rar – 67.2 MB
FILEAXA.COM – is our main file storage service. We host all files there. You can join the FILEAXA.COM premium service to access our all files without any limation and fast download speed.
