diff --git a/doc/guide/build.hpp b/doc/guide/build.hpp
index 6df10dd57e..6493bd0963 100644
--- a/doc/guide/build.hpp
+++ b/doc/guide/build.hpp
@@ -30,7 +30,7 @@ to build mlpack on Windows, see \ref build_windows (alternatively, you can read
is based on older versions).
You can download the latest mlpack release from here:
-mlpack-3.2.1
+mlpack-3.2.2
@section build_simple Simple Linux build instructions
@@ -38,9 +38,9 @@ Assuming all dependencies are installed in the system, you can run the commands
below directly to build and install mlpack.
@code
-$ wget https://www.mlpack.org/files/mlpack-3.2.1.tar.gz
-$ tar -xvzpf mlpack-3.2.1.tar.gz
-$ mkdir mlpack-3.2.1/build && cd mlpack-3.2.1/build
+$ wget https://www.mlpack.org/files/mlpack-3.2.2.tar.gz
+$ tar -xvzpf mlpack-3.2.2.tar.gz
+$ mkdir mlpack-3.2.2/build && cd mlpack-3.2.2/build
$ cmake ../
$ make -j4 # The -j is the number of cores you want to use for a build.
$ sudo make install
@@ -65,8 +65,8 @@ configure mlpack.
First we should unpack the mlpack source and create a build directory.
@code
-$ tar -xvzpf mlpack-3.2.1.tar.gz
-$ cd mlpack-3.2.1
+$ tar -xvzpf mlpack-3.2.2.tar.gz
+$ cd mlpack-3.2.2
$ mkdir build
@endcode
@@ -100,8 +100,15 @@ In Ubuntu and Debian, you can get all of these dependencies through apt:
@code
# apt-get install libboost-math-dev libboost-program-options-dev
libboost-test-dev libboost-serialization-dev libarmadillo-dev binutils-dev
- python-pandas python-numpy cython python-setuptools libensmallen-dev
- libstb-dev
+ python-pandas python-numpy cython python-setuptools
+@endcode
+
+If you are using Ubuntu 19.10 or newer, you can also install @c libensmallen-dev
+and @c libstb-dev, so that CMake does not need to automatically download those
+packages:
+
+@code
+# apt-get install libensmallen-dev libstb-dev
@endcode
On Fedora, Red Hat, or CentOS, these same dependencies can be obtained via dnf: