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[Русская версия](README-rus.md)
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### What is TopicNet?
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TopicNet is a high-level interface developed by [Machine Intelligence Laboratory](https://mipt.ai/en) for [BigARTM](https://github.com/bigartm/bigartm) library.
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```TopicNet``` library was created to assist in the task of building topic models. It aims at automating model training routine freeing more time for artistic process of constructing a target functional for the task at hand.
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Further you can read documentation [here](https://machine-intelligence-laboratory.github.io/TopicNet/). Currently we are in the process of imporving it.
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## How to install TopicNet
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**Core library functionality is based on BigARTM library** which required manual installation on all systems.
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Currently we have working solution for Linux users:
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```
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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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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 class.](topicnet/cooking_machine/dataset.py)
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display_html(line, raw=True)
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```
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## FAQ
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#### In the example we used to write vw modality like **@modality**, is it a VowpallWabbit format?
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