Set of examples of ML approaches implemented in C++ with different frameworks.
You can also consider taking a look at my book "Hands-On Machine Learning with C++" which covers also the theoretical part of algorithms and contains additional examples.
After cloning the source code please execute next commands to get all required third parties:
git submodule init
git submodule update
Each folder contains single example with own CMakeLists.txt file.
Linear Algebra
| Article | Library | CPU | GPU | Library's license |
|---|---|---|---|---|
| Polynomial regression | XTensor | + | BSD 3-Clause | |
| Polynomial regression | MShadow | + | + | Apache License 2.0 |
| Polynomial regression | Eigen | + | ? | Mozilla Public License 2.0 |
| planned | Armadillo | + | + | Apache License 2.0 |
Full featured frameworks
| Article | Library | CPU | GPU | Library's license |
|---|---|---|---|---|
| Classification | Shark-ML | + | + | LGPL |
| planned | mlpack | + | BSD 3-Clause, Mozilla Public License 2, Boost Software License 1.0 | |
| Classification | shogun-toolbox | + | + | BSD 3-Clause |
| Classification | Dlib | + | + | Boost Software License - Version 1.0 |
Deep Learning
| Article | Library | CPU | GPU | Library's license |
|---|---|---|---|---|
| Faster R-CNN | MXNet(sources) | + | + | Apache License 2.0 |
| planned | Caffe2(sources) | + | + | Apache License 2.0 |
| Mask R-CNN | PyTorch C++ Frontend | + | + | BSD 3-Clause |