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@@ -12,7 +12,8 @@ This repo is intended to be used by people that want to explore BigARTM function
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## How to install TopicNet
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**Core library functionality is based on BigARTM library** which requires manual installation.
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To avoid that you can use a [docker images](https://hub.docker.com/r/xtonev/bigartm/tags) with preinstalled topicnet libraries in them.
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To avoid that you can use [docker images](https://hub.docker.com/r/xtonev/bigartm/tags) with preinstalled BigARTM library in them.
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Alternatively, you can follow [BigARTM installation manual](https://bigartm.readthedocs.io/en/stable/installation/index.html)
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After setting up the environment you can fork this repository or use ```pip install topicnet``` to install the library.
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## How to use TopicNet
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Let's say you have a handful of raw text mined from some source and you want to perform some topic modelling on them. Where should you start?
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### Data Preparation
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As always before training data needs to be preprocessed. TopicNet does not perform data preprocessing itself. Instead, it demands data being prepared by the user and loaded via [Dataset (no link yet)]() class.
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Every ML problem starts with data preprocess step. TopicNet does not perform data preprocessing itself. Instead, it demands data being prepared by the user and loaded via [Dataset (no link yet)]() class.
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Here is a basic example of how one can achieve that:
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