Rationale | Custom grid creation | Setup | Usage | Data Preparation | Using grid_depth() | Tuning | Inspect | Visualizing Results | Finalizing the Model | Evaluating on the test set | A Note on Parametric Activations

Introduction | A complete example | General Workflow | i. Layout Model Definition | ii. Choose the test | iii. Execute and read the output | Eager form | Switching the estimation method | Hypothesis expressions | Conclusion | Learn More

Introduction | Installation | Before using | Main Features | What it doesn't support | Usage: Three Levels of Interaction | Level 1: Code Generation for torch::nn_module | Level 2: Direct Training Interface | Level 3: Conventional tidymodels Integration | Hyperparameter Tuning & Resampling | Variable Importance | Integration with | Learn More

Rationale | Installation | A Quick Tour | table_default() | table_summary() | corr_matrix() | cross_table() | Styling Primer

Rationale | Function to use | Basic Usage | Using Custom Activations in a Model | Skipping the Dry-Run Probe | Naming Your Custom Activation | Error Handling | Summary

What's so special about | Setup | Linear Regression as a Special Case | Data | Fitting the model | Evaluation | Comparison with lm() | Logistic Regression as a Special Case | Binary Logistic Regression | Comparison with glm() / nnet::multinom()

Similar packages | Package Comparison | Complementary Use