put items away

Author: Evgeny-Egorov-Projects

topicnet/demos/README.md

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 This section provides demonstrations of how to use this library in NLP tasks.
 
 `1-RTL-Wiki-Preprocessing` --  notebook describing how to get a wikipedia dataset and write data in VW format.
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 `2-RTL-Wiki-Building-Topic-Model` --  notebook with first steps to build topic model by consequently tuning it's hyperparameters
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 `3-Visualizing-Your-Model-Documents` -- notebook providing a fres outlook on unstructured document collection with the help of a topic model
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 `4-20NG-Preprocessing` -- preparing data from a well-know 20 Newsgroups dataset
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 `5-20NG-GenSim-vs-TopicNet` -- a comparisson between two topic models build by Gensim and TopicNet library. In the notebook we compare model topics by calculating their [UMass coherence measure](https://palmetto.demos.dice-research.org/) and using Jaccard measure to compare topic top-tokens diversity
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 `6-Postnauka-Building-Topic-Model` -- an analog of the RTL-Wiki notebook performed on the corpus of Russian pop-science articles given by postnauka.ru
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 `7-Postnauka-Recipe` -- a demonstration of rapid-prototyping methods provided by the library
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 `8-Coherence-Maximization-Recipe` -- a recipe for hyperparameter search in regard to custom Coherence metric
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 `9-Topic-Prior-Regularizer-Tutorial` -- a demonstration of the approach to learning topics from the unbalanced corpus
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 `10-Making-Decorrelation-and-Topic-Selection-Friends` -- reproduction of a very complicated experiment on automatically learning optimal number of topics from the collection. Hurdle is - both needed regularizers when working together nullify token-topic matrix.
 
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