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From Peter Stahl <pst...@pivotal.io>
Subject Re: [Announce] Apache MADlib v1.17.0 released
Date Fri, 10 Apr 2020 20:57:47 GMT
Congratulations!

On Fri, Apr 10, 2020 at 11:26 AM Nikhil Kak <nkak@pivotal.io> wrote:

> Great work team. Thank you Orhan once again for volunteering to be the
> release manager.
>
> On Fri, Apr 10, 2020 at 11:21 AM Frank McQuillan <fmcquillan@pivotal.io>
> wrote:
>
>> Thank you Orhan!
>>
>>
>>
>> On Fri, Apr 10, 2020 at 10:39 AM Orhan Kislal <okislal@pivotal.io> wrote:
>>
>>> The Apache MADlib team is pleased to announce the immediate
>>> availability of the 1.17.0 release.
>>>
>>> The main goals of this release are:
>>>
>>> New features
>>>     - DL: Add optional params to madlib_keras_fit_multiple_model
>>> (MADLIB-1397)
>>>     - DL: Fit and evaluate changes for asymmetric cluster config
>>> (MADLIB-1393)
>>>     - DL: Make param search fit() function work with existing evaluate
>>> and
>>> predict (MADLIB-1387)
>>>     - DL: ParamSearch: Add utility function for generating model
>>> selection
>>> table (MADLIB-1375)
>>>     - DL: Predict changes for asymmetric cluster config (MADLIB-1394)
>>>     - DL: Preprocessor should evenly distribute data on an arbitrary
>>> number
>>> of segments (MADLIB-1378)
>>>     - DL: Preprocessor support for asymmetric segment distribution
>>> (MADLIB-1392)
>>>     - DL: Remove model_arch_table column from the output of
>>> load_model_selection_table (MADLIB-1381)
>>>     - DL: Support DL predict without training on MADlib (MADLIB-1359)
>>>     - DL: Transfer learning for multi-model (MADLIB-1389)
>>>     - Kmeans: Add simple silhouette score for every point (MADLIB-1382)
>>>     - Kmeans: Select number of centroids in k-means (MADLIB-1380)
>>>     - PostgreSQL 12 support (MADLIB-1391)
>>>
>>> Improvements:
>>>     - Assoc rules: Add option to set number of posterior in association
>>> rules (MADLIB-1327)
>>>     - Correlation: Improve correlation and covariance memory usage with
>>> large number of groups (MADLIB-1301)
>>>     - DL: helper function for asymmetric cluster config (MADLIB-1390)
>>>     - DL: Mini-batch preprocessor for images - performance issue
>>> (MADLIB-1342)
>>>     - DL: Modify warm start logic for DL to handle case of missing weight
>>> (MADLIB-1400)
>>>     - DL: Param search for multiple models on MPP architecture
>>> (MADLIB-1386)
>>>     - DL: performance improvements to fit transition function
>>> (MADLIB-1418)
>>>     - Docs: Enhance Installation Guides (MADLIB-1399)
>>>     - Graph: SSSP should not show vertices in output table that are
>>> unreachable (MADLIB-1415)
>>>     - Knn - add zero check and output distance array (MADLIB-1370)
>>>     - LDA: Add stopping criteria on perplexity to LDA (MADLIB-1351)
>>>     - Summary: Last optional param in summary errors when NULL
>>> (MADLIB-1413)
>>>     - Summary: Summary function has dups for MFV for approximate results
>>> (MADLIB-1412)
>>>     - SVM: Change default num_components for SVM to max(100,
>>> 2*num_features) (MADLIB-1384)
>>>
>>> All release changes can be found here:
>>>
>>>   https://cwiki.apache.org/confluence/display/MADLIB/MADlib+1.17.0
>>>
>>> You can download the source release and convenience binary packages
>>> from Apache MADlib's download page here:
>>>
>>>   http://madlib.apache.org/download.html
>>>
>>> Alternatively, you can download through an ASF mirror near you:
>>>
>>>   https://www.apache.org/dyn/closer.lua/madlib/1.17.0
>>>
>>> ----
>>>
>>> Apache MADlib is an open-source library for scalable in-database
>>> analytics. It provides data-parallel implementations of mathematical,
>>> statistical and machine learning methods for structured and
>>> unstructured data.
>>>
>>> The MADlib mission: to foster widespread development of scalable
>>> analytic skills, by harnessing efforts from commercial practice,
>>> academic research, and open-source development.
>>>
>>> We welcome your help and feedback. For more information on how to
>>> report problems, and to get involved, visit the project website at
>>> https://madlib.apache.org
>>>
>>> ----
>>>
>>> Thank you, everyone, who contributed to the 1.17.0 release. We look
>>> forward to continued community participation for the next release!
>>>
>>> Regards,
>>> Orhan Kislal
>>>
>>
>
> --
> Thanks,
> Nikhil Kak
>

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