diff --git a/doc/guide/build.hpp b/doc/guide/build.hpp index d2bad62e41..cb993d5deb 100644 --- a/doc/guide/build.hpp +++ b/doc/guide/build.hpp @@ -28,7 +28,7 @@ to build mlpack on Windows, see Keon's excellent tutorial. You can download the latest mlpack release from here: -mlpack-3.0.1 +mlpack-3.0.2 @section build_simple Simple Linux build instructions @@ -36,9 +36,9 @@ Assuming all dependencies are installed in the system, you can run the commands below directly to build and install mlpack. @code -$ wget http://www.mlpack.org/files/mlpack-3.0.1.tar.gz -$ tar -xvzpf mlpack-3.0.1.tar.gz -$ mkdir mlpack-3.0.1/build && cd mlpack-3.0.1/build +$ wget http://www.mlpack.org/files/mlpack-3.0.2.tar.gz +$ tar -xvzpf mlpack-3.0.2.tar.gz +$ mkdir mlpack-3.0.2/build && cd mlpack-3.0.2/build $ cmake ../ $ make -j4 # The -j is the number of cores you want to use for a build. $ sudo make install @@ -63,8 +63,8 @@ configure mlpack. First we should unpack the mlpack source and create a build directory. @code -$ tar -xvzpf mlpack-3.0.1.tar.gz -$ cd mlpack-3.0.1 +$ tar -xvzpf mlpack-3.0.2.tar.gz +$ cd mlpack-3.0.2 $ mkdir build @endcode diff --git a/doc/guide/python_quickstart.hpp b/doc/guide/python_quickstart.hpp index 64cea4cc1e..d197f6f8d0 100644 --- a/doc/guide/python_quickstart.hpp +++ b/doc/guide/python_quickstart.hpp @@ -31,9 +31,9 @@ build and install mlpack. You can copy-paste the commands into your shell. @code{.sh} sudo apt-get install libboost-all-dev g++ cmake libarmadillo-dev python-pip wget sudo pip install cython setuptools distutils numpy pandas -wget http://www.mlpack.org/files/mlpack-3.0.1.tar.gz -tar -xvzpf mlpack-3.0.1.tar.gz -mkdir -p mlpack-3.0.1/build/ && cd mlpack-3.0.1/build/ +wget http://www.mlpack.org/files/mlpack-3.0.2.tar.gz +tar -xvzpf mlpack-3.0.2.tar.gz +mkdir -p mlpack-3.0.2/build/ && cd mlpack-3.0.2/build/ cmake ../ && make -j4 && sudo make install @endcode