mlpack has a number of examples, video tutorials, and other resources showing usage of the library.
- mlpack examples repository: contains simple examples of mlpack usage for various machine learning tasks, in C++ and other languages. Both notebooks and standalone programs are available.
- mlpack Youtube channel: tutorial videos
for getting started with mlpack.
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Installing mlpack for use in C++: a step-by-step tutorial for installing and using mlpack from C++.
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Using mlpack for command-line data science: a demonstration of mlpack's command-line bindings.
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Simple data science workflow in C++ with mlpack: a tutorial using random forests and softmax regression in C++ to solve a simple data science problem.
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Development workflow tutorial: VSCode: set up an mlpack development environment in VSCode. This is useful if you are interested in contributing to mlpack.
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Development workflow tutorial: command-line: set up an mlpack development environment from the command-line. This is useful if you are interested in contributing to mlpack.
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- mlpack models repository: contains implementations of specific deep learning models that are too large or complex for inclusion in the main mlpack library.