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I work in a few directions:

  1. Support for popular search engine tool luke: https://github.com/DmitryKey/luke It has been incorporated into Apache Lucene starting 8.1, but all prior versions continue to need my attention.

  2. Teach search and NLP to students, sometimes unpaid: https://github.com/DmitryKey/kik-lg211-2018

  3. Support of other NLP frameworks and systems: https://github.com/boudinfl/pke/issues/80 https://github.com/wadimiusz/diachrony_for_russian/pull/5

  4. Popularizing NLP and Machine Learning: https://github.com/semanticanalyzer/weka-mnb-sentiment-analysis-template-project

  5. Making Text APIs affordable and easy to use for every developer: https://github.com/semanticanalyzer/nlproc_sdk_sample_code

Featured work

  1. DmitryKey/luke

    This is mavenised Luke: Lucene Toolbox Project

    Java 1,534
  2. DmitryKey/MTengine

    Crowdsource machine translation to every house

    Python 2
  3. DmitryKey/kaggle_stackexchange_prediction

    This is source code of submission by SkyNet team for the StackExchange contest of closed question prediction.

    Python 1
  4. DmitryKey/nlp-spam

    Ruby classifier for classifying spam on a social network using NLP.

    Ruby 1
  5. DmitryKey/luke-gwt

    GWT UI for luke Lucene Toolbox

    Java 2
  6. DmitryKey/simplenlg

    Automatically exported from code.google.com/p/simplenlg

    Java 1

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I'd like to begin working on a Deep Learning course, based on several sources, like books and courses I have studied and based on my own experience with DL in application to text processing and analysis.

The target is to teach this course at the University of Helsinki for bachelor / master degree level.