Practical Machine Learning with the mtcars Dataset in R | CodeSignal Learn

Practical Machine Learning with the mtcars Dataset in R | CodeSignal Learn

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Basic Introduction to Data Science with R
Practical Machine Learning with the mtcars Dataset in R

Practical Machine Learning with the mtcars Dataset in R

Put your data science skills into practice by working on machine learning projects using the classic `mtcars` dataset in R. This course provides hands-on experience with end-to-end solutions, from data preprocessing to model evaluation, ensuring you are prepared for real-world tasks.

Lessons and practices

Lesson 1: Preprocessing and Exploring the mtcars Dataset

Adapting Data Preprocessing Routine

Fix the Data Preprocessing Bug

Data Exploration with mtcars

Preprocessing with Mean Calculation

Exploring the mtcars Dataset

Lesson 2: Splitting the Data and Feature Scaling

Change the Data Split Ratio

Find and Fix the Errors

Fill in the Missing Code

Splitting and Scaling in R

Split and Scale Your Data

Lesson 3: Building and Evaluating a Model

Change Logistic Model Prediction

Fix Bug in Logistic Model

Train a Binary Classifier Model

Train a New Logistic Model

Multiclass Logistic Regression in R

Lesson 4: Making Predictions and Evaluating Performance

Switch to Random Forest Model

Fix the Prediction Code

Making Predictions and Evaluation

Evaluating Model Predictions

Write Code to Do Predictions and Evaluate

Lesson 5: Visualizing Model Results and Feature Importance

Plot Theme Comparison

Fix the Logistic Regression Plot

Add Missing Parts for Visualization

Visualize Logistic Regression Coefficients

Visualize Variable Importance

Lesson 6: Generalizing and Validating Models with Cross-Validation

Modify Cross-Validation Folds

Fix Cross-Validation Code

Cross-Validate with Seven Folds

Cross-Validation From Scratch

Interested in this course? Learn and practice with Cosmo!

Practice is how you turn knowledge into actual skills.