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