# Examples Reference
This page provides a complete reference for all `cargo run --example` commands available in Aprender.
## Quick Reference
| `logistic_regression` | Binary classification | Supervised |
| `decision_tree_iris` | Decision tree classifier | Supervised |
| `random_forest_iris` | Random forest classifier | Supervised |
| `gbm_iris` | Gradient boosting classifier | Supervised |
| `naive_bayes_iris` | Naive Bayes classifier | Supervised |
| `knn_iris` | K-nearest neighbors | Supervised |
| `svm_iris` | Support vector machine | Supervised |
| `iris_clustering` | K-means on Iris dataset | Unsupervised |
| `pca_iris` | Dimensionality reduction | Unsupervised |
| `time_series_forecasting` | ARIMA forecasting | Time Series |
| `text_preprocessing` | NLP text processing | NLP |
| `qwen_chat` | Qwen2 LLM configuration demo | Deep Learning |
| `rosetta_stone` | Universal format converter | Model Ops |
| `model_merge_strategies` | SLERP/TIES/DARE model merging | Model Ops |
## Running Examples
### Basic Usage
```bash
# Run with default settings
cargo run --example <name>
# Run in release mode (10-20x faster)
cargo run --example <name> --release
# With feature flags
cargo run --example <name> --features inference
# With arguments
cargo run --example <name> -- arg1 arg2
```
## Supervised Learning
### Regression
```bash
cargo run --example regularized_regression --release
cargo run --example boston_housing --release
cargo run --example decision_tree_regression --release
cargo run --example random_forest_regression --release
```
### Classification
```bash
cargo run --example logistic_regression --release
cargo run --example decision_tree_iris --release
cargo run --example random_forest_iris --release
cargo run --example gbm_iris --release
cargo run --example naive_bayes_iris --release
cargo run --example knn_iris --release
cargo run --example svm_iris --release
cargo run --example classification_training --release
```
### Bayesian Inference
```bash
cargo run --example bayesian_linear_regression --release
cargo run --example bayesian_logistic_regression --release
cargo run --example beta_binomial_inference --release
cargo run --example gamma_poisson_inference --release
cargo run --example dirichlet_multinomial_inference --release
cargo run --example normal_inverse_gamma_inference --release
```
### Generalized Linear Models
```bash
cargo run --example negative_binomial_glm --release
```
## Unsupervised Learning
### Clustering
```bash
cargo run --example iris_clustering --release
cargo run --example dbscan_clustering --release
cargo run --example hierarchical_clustering --release
cargo run --example gmm_clustering --release
cargo run --example spectral_clustering --release
cargo run --example automl_clustering --release
```
### Dimensionality Reduction
```bash
cargo run --example pca_iris --release
cargo run --example tsne_visualization --release
```
### Anomaly Detection
```bash
cargo run --example isolation_forest_anomaly --release
cargo run --example lof_anomaly --release
```
## Deep Learning
### Neural Networks
```bash
cargo run --example xor_training --release
cargo run --example neural_network_training --release
cargo run --example classification_training --release
cargo run --example mixture_of_experts --release
```
### LLM / Qwen2
```bash
# Qwen2 model configuration and tokenization demo
cargo run --example qwen_chat --release
# Qwen2 native APR format demo
cargo run --example qwen_apr_native --release
# Chat template rendering (ChatML, LLaMA, etc.)
cargo run --example chat_template --release
# HuggingFace model import
cargo run --example phi_hf_import --release
# Whisper transcription
cargo run --example whisper_transcribe --release --features inference
```
### Model Compression
```bash
cargo run --example pruning_magnitude --release
cargo run --example lottery_ticket_pruning --release
```
## Time Series
```bash
cargo run --example time_series_forecasting --release
```
## NLP / Text Processing
```bash
cargo run --example text_preprocessing --release
cargo run --example text_classification --release
cargo run --example nlp_advanced --release
cargo run --example topic_sentiment_analysis --release
```
## Graph Algorithms
```bash
cargo run --example graph_algorithms_comprehensive --release
cargo run --example graph_social_network --release
cargo run --example community_detection --release
cargo run --example logic_family_tree --release
```
## Optimization
### Gradient-Based
```bash
cargo run --example optimizer_demo --release
cargo run --example batch_optimization --release
cargo run --example convex_optimization --release
cargo run --example constrained_optimization --release
cargo run --example admm_optimization --release
```
### Metaheuristics
```bash
cargo run --example metaheuristics_optimization --release
cargo run --example aco_tsp --release
cargo run --example tabu_tsp --release
cargo run --example predator_prey_optimization --release
```
## Model Operations
### APR Format
```bash
cargo run --example apr_loading_modes --release
cargo run --example apr_inspection --release
cargo run --example apr_scoring --release
cargo run --example apr_cache --release
cargo run --example apr_embed --release
cargo run --example apr_with_metadata --release
cargo run --example apr_cli_commands --release
cargo run --example create_test_apr --release
cargo run --example create_test_transformer_apr --release
```
### Model Conversion
```bash
# Rosetta Stone universal format converter
cargo run --example rosetta_stone --release
# Validated tensor contracts (Poka-Yoke)
cargo run --example validated_tensors --release
cargo run --example poka_yoke_validation --release
```
### Model Merging
```bash
# All 5 merge strategies: Average, Weighted, SLERP, TIES, DARE
cargo run --example model_merge_strategies --release
```
### Model Serialization
```bash
cargo run --example model_serialization --release
cargo run --example shell_model_format --release
cargo run --example shell_encryption_demo --release --features format-encryption
```
### Binary Inspection
```bash
# Hex forensics — format-aware binary inspection
cargo run --example hex_forensics --release
```
## Data Processing
```bash
cargo run --example dataframe_basics --release
cargo run --example data_preprocessing_scalers --release
cargo run --example synthetic_data_generation --release
cargo run --example descriptive_statistics --release
cargo run --example bayesian_blocks_histogram --release
```
## Recommendations
```bash
cargo run --example recommend_content --release
```
## Pattern Mining
```bash
cargo run --example market_basket_apriori --release
```
## AutoML / Model Selection
```bash
cargo run --example automl_clustering --release
cargo run --example grid_search_tuning --release
cargo run --example cross_validation --release
```
## GPU / CUDA
```bash
cargo run --example cuda_backend --release
cargo run --example trueno_compute_integration --release
```
## Model Zoo
```bash
cargo run --example model_zoo --release
```
## Sovereign AI Stack
```bash
cargo run --example sovereign_stack --release
cargo run --example sovereign_offline --release
```
## Pipeline & Validation
```bash
cargo run --example pipeline_verification --release
cargo run --example poka_yoke_validation --release
```
## Online Learning
```bash
cargo run --example online_learning --release
```
## Code Analysis
```bash
cargo run --example code_analysis --release
```
## Benchmarks
```bash
cargo run --example bench_comparison --release
cargo run --example showcase_benchmark --release
cargo run --example mem_test --release
```
## QA / Falsification
```bash
cargo run --example qa_verify --release
cargo run --example qa_falsify --release
cargo run --example qa_run --release
cargo run --example qa_chat --release
cargo run --example qa_serve --release
```
## See Also
- [Case Studies](./boston-housing.md) — Detailed walkthroughs
- [APR CLI Tool](../tools/apr-cli.md) — Command-line interface
- [APR Format Specification](../tools/apr-spec.md) — Model format details