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.