# The Aprender Guide
[Introduction](./introduction.md)
# Getting Started
- [Installation](./getting-started/installation.md)
- [First Inference](./getting-started/first-inference.md)
- [First Training](./getting-started/first-training.md)
- [First Server](./getting-started/first-server.md)
# CLI Reference
- [Overview](./cli-reference/overview.md)
- [apr run](./cli-reference/apr-run.md)
- [apr serve](./cli-reference/apr-serve.md)
- [apr chat](./cli-reference/apr-chat.md)
- [apr finetune](./cli-reference/apr-finetune.md)
- [apr inspect](./cli-reference/apr-inspect.md)
- [apr validate](./cli-reference/apr-validate.md)
- [apr convert](./cli-reference/apr-convert.md)
- [apr pull](./cli-reference/apr-pull.md)
# Architecture
- [Monorepo Layout](./architecture/monorepo-layout.md)
- [Crate Map](./architecture/crate-map.md)
- [Provable Contracts](./architecture/provable-contracts.md)
# Cookbook
- [See apr-cookbook](./cookbook/index.md)
# EXTREME TDD Methodology
# Core Methodology
- [What is EXTREME TDD?](./methodology/what-is-extreme-tdd.md)
- [The RED-GREEN-REFACTOR Cycle](./methodology/red-green-refactor.md)
- [Test-First Philosophy](./methodology/test-first-philosophy.md)
- [Zero Tolerance Quality](./methodology/zero-tolerance.md)
# The RED Phase
- [Writing Failing Tests First](./red-phase/failing-tests-first.md)
- [Test Categories](./red-phase/test-categories.md)
- [Unit Tests](./red-phase/unit-tests.md)
- [Integration Tests](./red-phase/integration-tests.md)
- [Property-Based Tests](./red-phase/property-based-tests.md)
- [Verification Strategy](./red-phase/verification-strategy.md)
# The GREEN Phase
- [Minimal Implementation](./green-phase/minimal-implementation.md)
- [Making Tests Pass](./green-phase/making-tests-pass.md)
- [Avoiding Over-Engineering](./green-phase/avoiding-over-engineering.md)
- [The Simplest Thing That Works](./green-phase/simplest-thing.md)
# The REFACTOR Phase
- [Refactoring with Confidence](./refactor-phase/refactoring-with-confidence.md)
- [Code Quality Improvements](./refactor-phase/code-quality.md)
- [Performance Optimization](./refactor-phase/performance-optimization.md)
- [Documentation](./refactor-phase/documentation.md)
# Advanced Testing
- [Popperian Falsification](./advanced-testing/popperian-falsification.md)
- [Property-Based Testing](./advanced-testing/property-based-testing.md)
- [Proptest Fundamentals](./advanced-testing/proptest-fundamentals.md)
- [Strategies and Generators](./advanced-testing/strategies-generators.md)
- [Testing Invariants](./advanced-testing/testing-invariants.md)
- [Mutation Testing](./advanced-testing/mutation-testing.md)
- [What is Mutation Testing?](./advanced-testing/what-is-mutation-testing.md)
- [Using cargo-mutants](./advanced-testing/using-cargo-mutants.md)
- [Mutation Score Targets](./advanced-testing/mutation-score-targets.md)
- [Killing Mutants](./advanced-testing/killing-mutants.md)
- [Fuzzing](./advanced-testing/fuzzing.md)
- [Benchmark Testing](./advanced-testing/benchmark-testing.md)
# Quality Gates
- [Pre-Commit Hooks](./quality-gates/pre-commit-hooks.md)
- [Continuous Integration](./quality-gates/continuous-integration.md)
- [Code Formatting (rustfmt)](./quality-gates/code-formatting.md)
- [Linting (clippy)](./quality-gates/linting-clippy.md)
- [Coverage Measurement](./quality-gates/coverage-measurement.md)
- [Complexity Analysis](./quality-gates/complexity-analysis.md)
- [Technical Debt Gradient (TDG)](./quality-gates/tdg-score.md)
# Toyota Way Principles
- [Overview](./toyota-way/overview.md)
- [Kaizen (Continuous Improvement)](./toyota-way/kaizen.md)
- [Genchi Genbutsu (Go and See)](./toyota-way/genchi-genbutsu.md)
- [Jidoka (Built-in Quality)](./toyota-way/jidoka.md)
- [PDCA Cycle](./toyota-way/pdca-cycle.md)
- [Respect for People](./toyota-way/respect-for-people.md)
# Machine Learning Fundamentals
## Supervised Learning
- [Linear Regression Theory](./ml-fundamentals/linear-regression.md)
- [Regularization Theory](./ml-fundamentals/regularization.md)
- [Logistic Regression Theory](./ml-fundamentals/logistic-regression.md)
- [K-Nearest Neighbors (kNN) Theory](./ml-fundamentals/knn.md)
- [Naive Bayes Theory](./ml-fundamentals/naive-bayes.md)
- [Bayesian Inference Theory](./ml-fundamentals/bayesian-inference.md)
- [Support Vector Machines (SVM) Theory](./ml-fundamentals/svm.md)
- [Decision Trees Theory](./ml-fundamentals/decision-trees.md)
- [Ensemble Methods Theory](./ml-fundamentals/ensemble-methods.md)
## Unsupervised Learning
- [K-Means Clustering Theory](./ml-fundamentals/kmeans-clustering.md)
- [Principal Component Analysis (PCA) Theory](./ml-fundamentals/pca.md)
- [t-SNE (t-Distributed Stochastic Neighbor Embedding) Theory](./ml-fundamentals/tsne.md)
## Model Evaluation
- [Regression Metrics Theory](./ml-fundamentals/regression-metrics.md)
- [Classification Metrics Theory](./ml-fundamentals/classification-metrics.md)
- [Cross-Validation Theory](./ml-fundamentals/cross-validation.md)
## Optimization
- [Gradient Descent Theory](./ml-fundamentals/gradient-descent.md)
- [Advanced Optimizers Theory](./ml-fundamentals/advanced-optimizers.md)
- [Metaheuristics Theory](./ml-fundamentals/metaheuristics.md)
## AutoML
- [AutoML: Automated Machine Learning](./ml-fundamentals/automl.md)
## Learning Paradigms
- [Compiler-in-the-Loop Learning](./ml-fundamentals/compiler-in-the-loop.md)
- [Online Learning Theory](./ml-fundamentals/online-learning.md)
- [Neuro-Symbolic Reasoning Theory](./ml-fundamentals/neuro-symbolic.md)
- [Transfer Learning Theory](./ml-fundamentals/transfer-learning.md)
- [Active Learning Theory](./ml-fundamentals/active-learning.md)
- [Weak Supervision Theory](./ml-fundamentals/weak-supervision.md)
## Deep Learning
- [Automatic Differentiation Theory](./ml-fundamentals/automatic-differentiation.md)
- [Graph Neural Networks Theory](./ml-fundamentals/graph-neural-networks.md)
- [LoRA Fine-Tuning](./ml-fundamentals/fine-tuning.md)
## Model Compression
- [Neural Network Pruning Theory](./ml-fundamentals/neural-network-pruning.md)
- [Lottery Ticket Hypothesis Theory](./ml-fundamentals/lottery-ticket-hypothesis.md)
## Simulation and Risk
- [Monte Carlo Simulation Theory](./ml-fundamentals/monte-carlo.md)
## Speech and Voice
- [Speech and Voice Processing Theory](./ml-fundamentals/speech-voice-processing.md)
## Model Quality
- [Probability Calibration Theory](./ml-fundamentals/probability-calibration.md)
- [Chaos Engineering for ML](./ml-fundamentals/chaos-engineering.md)
## Deployment
- [WebAssembly for ML](./ml-fundamentals/webassembly-ml.md)
## Preprocessing
- [Feature Scaling Theory](./ml-fundamentals/feature-scaling.md)
## Audio Processing
- [Audio Processing Theory](./ml-fundamentals/audio-processing.md)
## Graph Algorithms
- [Graph Algorithms Theory](./ml-fundamentals/graph-algorithms.md)
- [Graph Pathfinding Theory](./ml-fundamentals/graph-pathfinding.md)
- [Graph Components and Traversal](./ml-fundamentals/graph-components-traversal.md)
- [Graph Link Prediction and Community Detection](./ml-fundamentals/graph-link-prediction.md)
## Statistics
- [Descriptive Statistics Theory](./ml-fundamentals/descriptive-statistics.md)
## Pattern Mining
- [Apriori Algorithm Theory](./ml-fundamentals/apriori.md)
# Real-World Examples from Aprender
- [Examples Reference](./examples/examples-reference.md)
- [Case Study: Linear Regression](./examples/linear-regression.md)
- [Case Study: Boston Housing](./examples/boston-housing.md)
- [Case Study: Cross-Validation](./examples/cross-validation.md)
- [Case Study: Grid Search Hyperparameter Tuning](./examples/grid-search-tuning.md)
- [Case Study: AutoML Clustering (TPE)](./examples/automl-clustering.md)
- [Case Study: Random Forest](./examples/random-forest.md)
- [Case Study: Random Forest Iris](./examples/random-forest-iris.md)
- [Case Study: Random Forest Regression](./examples/random-forest-regression.md)
- [Case Study: Decision Tree Iris](./examples/decision-tree-iris.md)
- [Case Study: Decision Tree Regression](./examples/decision-tree-regression.md)
- [Case Study: Model Serialization](./examples/model-serialization.md)
- [Case Study: Model Format (.apr)](./examples/model-format.md)
- [The .apr Format: A Five Whys Deep Dive](./examples/apr-format-deep-dive.md)
- [Case Study: Model Bundling and Memory Paging](./examples/model-bundling-paging.md)
- [Case Study: Tracing Memory Paging with Renacer](./examples/tracing-memory-paging.md)
- [Case Study: Bundle Trace Demo](./examples/bundle-trace-demo.md)
- [Case Study: Synthetic Data Generation](./examples/synthetic-data-generation.md)
- [Case Study: Code-Aware EDA](./examples/code-eda.md)
- [Case Study: Code Feature Extraction](./examples/code-feature-extractor.md)
- [Case Study: Code Analysis with Code2Vec and MPNN](./examples/code-analysis.md)
- [Case Study: KMeans Clustering](./examples/kmeans-clustering.md)
- [Case Study: DBSCAN Clustering](./examples/dbscan-clustering.md)
- [Case Study: Hierarchical Clustering](./examples/hierarchical-clustering.md)
- [Case Study: GMM Clustering](./examples/gmm-clustering.md)
- [Case Study: Iris Clustering](./examples/iris-clustering.md)
- [Case Study: Logistic Regression](./examples/logistic-regression.md)
- [Case Study: KNN Iris](./examples/knn-iris.md)
- [Case Study: Naive Bayes Iris](./examples/naive-bayes-iris.md)
- [Case Study: Beta-Binomial Bayesian Inference](./examples/beta-binomial-inference.md)
- [Case Study: Gamma-Poisson Bayesian Inference](./examples/gamma-poisson-inference.md)
- [Case Study: Normal-InverseGamma Bayesian Inference](./examples/normal-inverse-gamma-inference.md)
- [Case Study: Dirichlet-Multinomial Bayesian Inference](./examples/dirichlet-multinomial-inference.md)
- [Case Study: Bayesian Linear Regression](./examples/bayesian-linear-regression.md)
- [Case Study: Bayesian Logistic Regression](./examples/bayesian-logistic-regression.md)
- [Case Study: Negative Binomial GLM (Overdispersed Counts)](./examples/negative-binomial-glm.md)
- [Case Study: SVM Iris](./examples/svm-iris.md)
- [Case Study: Gradient Boosting Iris](./examples/gbm-iris.md)
- [Case Study: Regularized Regression](./examples/regularized-regression.md)
- [Case Study: Optimizer Demo](./examples/optimizer-demo.md)
- [Case Study: Batch Optimization](./examples/batch-optimization.md)
- [Case Study: Convex Optimization (FISTA + Coordinate Descent)](./examples/convex-optimization.md)
- [Case Study: Constrained Optimization (Projected GD + Augmented Lagrangian + Interior Point)](./examples/constrained-optimization.md)
- [Case Study: ADMM Optimization (Distributed ML + Federated Learning)](./examples/admm-optimization.md)
- [Case Study: Differential Evolution (Metaheuristics)](./examples/differential-evolution.md)
- [Case Study: Metaheuristics Optimization](./examples/metaheuristics-optimization.md)
- [Case Study: Ant Colony Optimization (TSP)](./examples/aco-tsp.md)
- [Case Study: Tabu Search (TSP)](./examples/tabu-tsp.md)
- [Case Study: aprender-tsp Sub-Crate](./examples/tsp-solver-crate.md)
- [Case Study: Predator-Prey Optimization](./examples/predator-prey-optimization.md)
- [Case Study: DataFrame Basics](./examples/dataframe-basics.md)
- [Case Study: Data Preprocessing with Scalers](./examples/data-preprocessing-scalers.md)
- [Case Study: PII Filtering for Fine-Tuning](./examples/pii-filtering.md)
- [Case Study: Evolutionary Merge Optimization](./examples/evolutionary-merge.md)
- [Case Study: Advanced Distillation Strategies](./examples/distillation-advanced.md)
- [Case Study: Continual Pre-Training](./examples/continual-pretraining.md)
- [Case Study: Direct Preference Optimization](./examples/dpo-preference.md)
- [Case Study: Evaluation Harness](./examples/eval-harness.md)
- [Case Study: Advanced Merge Strategies](./examples/advanced-merge.md)
- [Case Study: Differentiable Adaptive Merging (DAM)](./examples/dam-merge.md)
- [Case Study: RLVR (Verifiable Rewards)](./examples/rlvr.md)
- [Case Study: MoE Construction](./examples/moe-construction.md)
- [Case Study: Tokenizer Surgery](./examples/tokenizer-surgery.md)
- [Case Study: Per-Layer Merge](./examples/per-layer-merge.md)
- [Case Study: Graph Social Network](./examples/graph-social-network.md)
- [Case Study: Community Detection with Louvain](./examples/community-detection.md)
- [Case Study: Comprehensive Graph Algorithms](./examples/graph-algorithms-comprehensive.md)
- [Case Study: Descriptive Statistics](./examples/descriptive-statistics.md)
- [Case Study: Bayesian Blocks Histogram](./examples/bayesian-blocks-histogram.md)
- [Case Study: PCA Iris](./examples/pca-iris.md)
- [Case Study: Isolation Forest Anomaly Detection](./examples/isolation-forest-anomaly.md)
- [Case Study: Local Outlier Factor (LOF)](./examples/lof-anomaly.md)
- [Case Study: Spectral Clustering](./examples/spectral-clustering.md)
- [Case Study: t-SNE Visualization](./examples/tsne-visualization.md)
- [Case Study: Market Basket Analysis (Apriori)](./examples/market-basket-apriori.md)
- [Case Study: ARIMA Time Series Forecasting](./examples/time-series-forecasting.md)
- [Case Study: Text Preprocessing for NLP](./examples/text-preprocessing.md)
- [Case Study: Text Classification with TF-IDF](./examples/text-classification.md)
- [Case Study: Chat Templates for LLM Inference](./examples/chat-template.md)
- [Case Study: Advanced NLP (Similarity, Entities, Summarization)](./examples/advanced-nlp.md)
- [Case Study: XOR Neural Network (Deep Learning)](./examples/xor-neural-network.md)
- [Case Study: XOR Training](./examples/xor-training.md)
- [Case Study: Neural Network Training Pipeline](./examples/neural-network-training.md)
- [Case Study: Classification Training](./examples/classification-training.md)
- [Case Study: Advanced NLP](./examples/nlp-advanced.md)
- [Case Study: Topic & Sentiment Analysis](./examples/topic-sentiment-analysis.md)
- [Case Study: Content-Based Recommendations](./examples/recommend-content.md)
- [Case Study: Content-Based Recommender System](./examples/content-recommender.md)
- [Case Study: AI Shell Completion](./examples/shell-completion.md)
- [Case Study: Shell Completion Benchmarks](./examples/shell-completion-benchmarks.md)
- [Case Study: Publishing Shell Models to HF Hub](./examples/shell-hf-hub-publishing.md)
- [Case Study: Model Encryption Tiers](./examples/shell-encryption-tiers.md)
- [Case Study: Shell Encryption Demo](./examples/shell-encryption-demo.md)
- [Case Study: Shell Homomorphic Encryption](./examples/shell-homomorphic-encryption.md)
- [Case Study: Shell Model Format](./examples/shell-model-format.md)
- [Case Study: Mixture of Experts (MoE)](./examples/mixture-of-experts.md)
- [Developer's Guide: Shell History Models](./examples/shell-history-developer-guide.md)
- [Building Custom Error Classifiers](./examples/custom-error-classifier.md)
- [Case Study: CITL Automated Program Repair](./examples/citl-automated-repair.md)
- [Case Study: Batuta - Automated Migration to Aprender](./examples/batuta-integration.md)
- [Case Study: Online Learning and Dynamic Retraining](./examples/online-learning.md)
- [Case Study: APR Loading Modes](./examples/apr-loading-modes.md)
- [Case Study: APR Model Inspection](./examples/apr-inspection.md)
- [Case Study: APR 100-Point Quality Scoring](./examples/apr-scoring.md)
- [Case Study: APR Poka-Yoke Validation](./examples/poka-yoke-validation.md)
- [Case Study: APR Model Cache](./examples/apr-cache.md)
- [Case Study: APR Data Embedding](./examples/apr-embed.md)
- [Case Study: APR with JSON Metadata](./examples/apr-with-metadata.md)
- [Case Study: CUDA and GPU Backends](./examples/cuda-backend.md)
- [Case Study: Trueno Compute Integration](./examples/trueno-compute-integration.md)
- [Case Study: APR CLI Tool Demo](./examples/apr-cli-demo.md)
- [Case Study: Create Test APR Files](./examples/create-test-apr.md)
- [Case Study: APR CLI Commands Demo](./examples/apr-cli-commands.md)
- [Case Study: Model Zoo](./examples/model-zoo.md)
- [Case Study: Sovereign AI Stack Integration](./examples/sovereign-stack.md)
- [Case Study: Sovereign AI Offline Mode](./examples/sovereign-offline.md)
- [Case Study: Model Explainability and Audit Trails](./examples/explainability-audit.md)
- [Case Study: Model Serving](./examples/model-serving.md)
- [Case Study: Federation Gateway](./examples/federation-gateway.md)
- [Case Study: Federation Routing Policies](./examples/federation-routing.md)
- [Case Study: Probar TUI Testing](./examples/probar-tui-testing.md)
- [Case Study: Pipeline Verification](./examples/pipeline-verification.md)
- [Case Study: State Machine Playbooks](./examples/state-machine-playbooks.md)
- [Case Study: TensorLogic Neuro-Symbolic Reasoning](./examples/tensorlogic-reasoning.md)
- [Case Study: Audio Mel Spectrogram Processing](./examples/audio-mel-spectrogram.md)
- [Case Study: Monte Carlo Financial Simulation](./examples/monte-carlo-simulation.md)
- [Case Study: Automatic Differentiation Training](./examples/autograd-training.md)
- [Case Study: Graph Neural Networks](./examples/gnn-node-classification.md)
- [Case Study: Magnitude Pruning](./examples/pruning-magnitude.md)
- [Case Study: Lottery Ticket Pruning](./examples/lottery-ticket-pruning.md)
- [Case Study: Benchmark Comparison](./examples/bench-comparison.md)
- [Case Study: Showcase Benchmark](./examples/showcase-benchmark.md)
- [Case Study: QA Falsification Protocol](./examples/qa-falsification.md)
- [Case Study: Qwen2.5-Coder QA Playbook](./examples/qwen-qa-playbook.md)
- [Case Study: PTX Parity Validation (GH-219)](./examples/ptx-parity-validation.md)
- [Case Study: Hex Forensics — Binary Model Inspection](./examples/hex-forensics.md)
- [Case Study: Rosetta Stone — Universal Format Converter](./examples/rosetta-stone.md)
- [Case Study: Validated Tensors — Compile-Time Contracts](./examples/validated-tensors.md)
- [Case Study: Qwen Inference with realizar](./examples/qwen-inference.md)
- [Case Study: Sharded SafeTensors Serving (GH-213)](./examples/sharded-safetensors-serve.md)
- [Case Study: Model Merge Strategies (GH-245)](./examples/model-merge-strategies.md)
- [Case Study: Qwen3.5 Hybrid Attention (GH-278)](./examples/qwen3.5-hybrid-attention.md)
- [Case Study: cbtop Profiling Falsification (GH-420)](./examples/cbtop-profiling-falsification.md)
- [Case Study: APR Checkpoint Lifecycle](./examples/apr-checkpoint-lifecycle.md)
- [Case Study: BPE Tokenizer Benchmark](./examples/bench-bpe.md)
- [Case Study: Conv Layout Dogfood](./examples/conv-layout-dogfood.md)
- [Case Study: Create Test Transformer APR](./examples/create-test-transformer-apr.md)
- [Case Study: Data Quality Pipeline](./examples/data-quality-pipeline.md)
- [Case Study: Design by Contract](./examples/design-by-contract.md)
- [Case Study: GPU Fallback Dogfood](./examples/gpu-fallback-dogfood.md)
- [Case Study: Publish Shell Safety Model](./examples/publish-shell-safety.md)
- [Case Study: QA Chat Falsification](./examples/qa-chat.md)
- [Case Study: QA Infrastructure Falsification](./examples/qa-falsify.md)
- [Case Study: QA Run Falsification](./examples/qa-run.md)
- [Case Study: QA Serve Falsification](./examples/qa-serve.md)
- [Case Study: QA Codebase Verification](./examples/qa-verify.md)
- [Case Study: Shell Safety Inference](./examples/shell-safety-inference.md)
- [Case Study: Shell Safety Training](./examples/shell-safety-training.md)
- [Case Study: Logic Family Tree](./examples/logic-family-tree.md)
- [Case Study: Memory Test (Full)](./examples/mem-test-full.md)
- [Case Study: Memory Test](./examples/mem-test.md)
- [Case Study: Phi HuggingFace Import](./examples/phi-hf-import.md)
- [Case Study: Qwen APR Native](./examples/qwen-apr-native.md)
- [Case Study: Qwen Chat](./examples/qwen-chat.md)
- [Case Study: Whisper Transcribe](./examples/whisper-transcribe.md)
# Sprint-Based Development
- [Sprint Planning](./sprints/sprint-planning.md)
- [Sprint Execution](./sprints/sprint-execution.md)
- [Sprint Review](./sprints/sprint-review.md)
- [Sprint Retrospective](./sprints/sprint-retrospective.md)
- [Issue Management](./sprints/issue-management.md)
# Anti-Hallucination Enforcement
- [Test-Backed Examples](./anti-hallucination/test-backed-examples.md)
- [Example Verification](./anti-hallucination/example-verification.md)
- [CI Validation](./anti-hallucination/ci-validation.md)
- [Documentation Testing](./anti-hallucination/documentation-testing.md)
# Tools and Setup
- [Development Environment](./tools/development-environment.md)
- [cargo test](./tools/cargo-test.md)
- [cargo clippy](./tools/cargo-clippy.md)
- [cargo fmt](./tools/cargo-fmt.md)
- [cargo mutants](./tools/cargo-mutants.md)
- [proptest](./tools/proptest.md)
- [criterion](./tools/criterion.md)
- [pmat (Toyota AI Toolkit)](./tools/pmat.md)
- [apr (APR Model Operations CLI)](./tools/apr-cli.md)
- [APR Format Specification](./tools/apr-spec.md)
# Best Practices
- [Error Handling](./best-practices/error-handling.md)
- [API Design](./best-practices/api-design.md)
- [Builder Pattern](./best-practices/builder-pattern.md)
- [Type Safety](./best-practices/type-safety.md)
- [Performance Considerations](./best-practices/performance.md)
- [Documentation Standards](./best-practices/documentation-standards.md)
# Metrics and Measurement
- [Test Coverage](./metrics/test-coverage.md)
- [Mutation Score](./metrics/mutation-score.md)
- [Cyclomatic Complexity](./metrics/cyclomatic-complexity.md)
- [Code Churn](./metrics/code-churn.md)
- [Build Times](./metrics/build-times.md)
- [TDG Score Breakdown](./metrics/tdg-breakdown.md)
# Common Pitfalls
- [Skipping Tests](./pitfalls/skipping-tests.md)
- [Insufficient Test Coverage](./pitfalls/insufficient-coverage.md)
- [Ignoring Warnings](./pitfalls/ignoring-warnings.md)
- [Over-Mocking](./pitfalls/over-mocking.md)
- [Flaky Tests](./pitfalls/flaky-tests.md)
- [Technical Debt Accumulation](./pitfalls/technical-debt.md)
# Appendix
- [Glossary](./appendix/glossary.md)
- [References](./appendix/references.md)
- [Further Reading](./appendix/further-reading.md)
- [Contributing to This Book](./appendix/contributing.md)