### Introductory Tutorials

These tutorials introduce the basic concepts of working with mlpack, aimed at
developers who want to use and contribute to mlpack but are not sure where to
start.

 - [Building mlpack From Source ](doxygen/build.html)
 - [Building mlpack From Source on Windows ](doxygen/build_windows.html)
 - [File formats and loading data in mlpack ](doxygen/formatdoc.html)
 - [Matrices in mlpack ](doxygen/matrices.html)
 - [Writing an mlpack binding ](doxygen/iodoc.html)
 - [mlpack Timers ](doxygen/timer.html)
 - [Simple Sample mlpack Programs ](doxygen/sample.html)
 - [Sample C++ ML App for Windows ](doxygen/sample_ml_app.html)

### Method-specific Tutorials

These tutorials introduce the various methods mlpack offers, aimed at users who
want to get started quickly.  These tutorials start with simple examples and
progress to complex, extensible uses.

 - [NeighborSearch tutorial (k-nearest-neighbors) ](doxygen/nstutorial.html)
 - [Linear/ridge regression tutorial (mlpack_linear_regression) ](doxygen/lrtutorial.html)
 - [RangeSearch tutorial (mlpack_range_search) ](doxygen/rstutorial.html)
 - [Density Estimation Tree (DET) tutorial ](doxygen/dettutorial.html)
 - [K-Means tutorial (kmeans) ](doxygen/kmtutorial.html)
 - [Fast max-kernel search tutorial (fastmks) ](doxygen/fmkstutorial.html)
 - [EMST Tutorial ](doxygen/emst_tutorial.html)
 - [Alternating Matrix Factorization tutorial ](doxygen/amftutorial.html)
 - [Collaborative filtering tutorial ](doxygen/cftutorial.html)
 - [Approximate furthest neighbor search (mlpack_approx_kfn) tutorial ](doxygen/akfntutorial.html)
 - [Neural Network tutorial ](doxygen/anntutorial.html)

### Advanced Tutorials

These tutorials discuss some of the more advanced functionality contained in
mlpack.

 - [mlpack automatic bindings to other languages ](doxygen/bindings.html)
 - [Cross-Validation ](doxygen/cv.html)
 - [Hyper-Parameter Tuning ](doxygen/hpt_guide.html)

### Policy Class Documentation

mlpack uses templates to achieve its genericity and flexibility.  Some of the
template types used by mlpack are common across multiple machine learning
algorithms.  The links below provide documentation for some of these common
types.

 - [The MetricType policy in mlpack ](doxygen/metrics.html)
 - [The KernelType policy in mlpack ](doxygen/kernels.html)
 - [The TreeType policy in mlpack ](doxygen/trees.html)