elpa-delight
Emacs utility to customise the mode line
Emacs add-on 'delight' provides functionality to customise the
mode names displayed in the mode line.
libvirt-daemon-driver-lxc
Virtualization daemon LXC connection driver
libvirt exposes a long-term stable API that can be used to interact with
various hypervisors. Its architecture is highly modular, with most features
implemented as optional drivers. It can be used from C as well as several
other programming languages, and it forms the basis of virtualization
solutions tailored for a range of use cases.
libmarc-fast-perl
fast implementation of MARC database reader
Marc::Fast is a very fast alternative to the MARC and MARC::Record modules.
It's is also very suitable for random access to MARC records (as opposed to
sequential one).
gobjc++-14-multilib-x86-64-linux-gnu
GNU Objective-C++ compiler (multilib support)
This is the GNU Objective-C++ compiler, which compiles Objective-C++ on
platforms supported by the gcc compiler.
python3-vigra
Python3 bindings for the C++ computer vision library
Vision with Generic Algorithms (VIGRA) is a computer vision library
that puts its main emphasis on flexible algorithms, because
algorithms represent the principle know-how of this field. The
library was consequently built using generic programming as
introduced by Stepanov and Musser and exemplified in the C++ Standard
Template Library. By writing a few adapters (image iterators and
accessors) you can use VIGRA's algorithms on top of your data
structures, within your environment.
libxgboost0
Scalable and Flexible Gradient Boosting (Shared lib)
XGBoost is an optimized distributed gradient boosting library designed to be
highly efficient, flexible and portable. It implements machine learning
algorithms under the Gradient Boosting framework. XGBoost provides a parallel
tree boosting (also known as GBDT, GBM) that solve many data science problems
in a fast and accurate way. The same code runs on major distributed environment
(Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of
examples.