[mlpack] mlpack 2.0.0 released

[Ajinkya Kale]

Congratulations all on 2.0.0 release!
Do we have a page on who and where all is mlpack used ?

On Thu, Dec 24, 2015, 08:20 Ryan Curtin <ryan at ratml.org> wrote:

> Hello there,
>
> This has been a long time coming...
>
> Last night I tagged mlpack-2.0.0 and uploaded it to the mlpack website.
> You can get it here:
>
>   http://www.mlpack.org/files/mlpack-2.0.0.tar.gz
>
> There has been a significant amount of refactoring and hard work by lots
> of people since the last release in January, and the changelog is fairly
> long, so I'll put what I think are the most exciting bits below:
>
>  * Parallelization: the DET (density estimation trees) code is now
>    parallelized with OpenMP.  As time goes on, parallelization will be
>    added to other algorithms, but note that you can also use Armadillo
>    with OpenBLAS, which will parallelize all the linear algebra calls.
>
>  * Model saving and loading: where appropriate, all of the command-line
>    programs now support loading and saving models.  So you can train,
>    say, a logistic regression model, and save it for later use.  This is
>    also possible with techniques like all-k-nearest-neighbor search,
>    which allow you to save the tree built on the points.  Model
>    serialization support is also available from C++, too, of course.
>
>  * Significant refactoring: most machine learning algorithms now follow
>    the same API, and documentation has been improved.
>
>  * Tree-based algorithms now support multiple types of trees in a far
>    easier manner.
>
>  * The k-means code now supports five different algorithms, many of them
>    far faster than the original implementation.
>
>  * Add streaming decision trees (Hoeffding trees) for fast classifiers
>    on huge datasets.  This supports both categorical and numeric
>    features.
>
>  * No more dependence on libxml2; boost::serialization is used instead.
>
>  * Armadillo minimum version bump to 4.100.0.
>
>  * All mlpack programs are now prefixed with 'mlpack_', so for instance
>    'allknn' is now 'mlpack_allknn'.
>
> Also exciting, in my opinion, is the community that has grown around
> mlpack.  Here are some neat and interesting statistics:
>
>  * mlpack has almost 40 contributors
>
>  * mlpack has now been downloaded at least 35k+ times (my logs
>    undercount)
>
>  * mlpack has been used in at least 40 academic papers (also a lowball
>    estimate)---and this number is increasing faster and faster
>
>  * the mlpack codebase now contains about 60k source lines of code
>    (SLOC)
>
> So I have to say, I'm very happy that we have built tools that people
> are finding useful!  I hope that this trend continues. :)
>
> For the full changelog in mlpack-2.0.0, see
> http://www.mlpack.org/history.html.  Over the next few days/weeks,
> updated mlpack packages will be pushed to the package repositories of
> various distributions.
>
> Lastly, some notes about the future.  Upcoming releases will follow the
> versioning guidelines now present in UPDATING.txt (semantic versioning):
> https://github.com/mlpack/mlpack/blob/master/UPDATING.txt
>
> Future goals include a flexible framework for artificial neural networks
> (prototype code can currently be found in the master branch in
> src/mlpack/methods/ann), generic bindings to other languages such as
> Python, Java, MATLAB, and others, parallelization support for more
> algorithms via OpenMP, a new implementation of random forests, and
> dimensionality reduction or manifold learning techniques.
>
> I'm also hopeful that we can have a much more frequent release cycle,
> more like once a month or more, following the versioning guidelines I
> mentioned earlier.
>
> So, I hope that you find this release useful!  Please feel free to
> report any bugs as Github issues to https://github.com/mlpack/mlpack or
> to this mailing list, or to the #mlpack channel in freenode.
>
> --
> Ryan Curtin    | "Good Lord - I've heard about this - cat juggling!
> ryan at ratml.org | Stop! Stop! Stop it!" - Navin R. Johnson
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>
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