Topic analysis using neural networks

This repository was created for my diploma thesis. It consists of two modified repositories https://github.com/MarekUlip/TopicAnalysisDeep and https://github.com/MarekUlip/topic-analysis .

Requirements

Scripts were written using Python 3.7
tensorflow 2.1 gpu (view installation for details also note that scripts using generators will not run in earlier versions because some of them use fit with generators which were not supported until 2.1)

Installation

All install lines are intended for Anaconda environment. So first make sure that Anaconda is up and running on your machine.
From Anaconda Prompt type following lines:
conda create --name tensorflow20
conda activate tensorflow20

After activating the anaconda environment you can start installing required packages:

Installing tensorflow

conda install -c anaconda tensorflow-gpu

General helpful libraries

These libraries have helpful methods for analysis or showing results
conda install -c conda-forge matplotlib
conda install -c anaconda scikit-learn

Pydot and graphviz are used to generate neural network architecture image conda install -c anaconda pydot
conda install -c anaconda graphviz (May not be needed as pydot should be installed with it)

Libraries for hyperparameter search

Hyperas can be installed only via pip so pip
conda install pip
pip install hyperas

Libraries used for text analysis

conda install -c anaconda gensim
conda install -c conda-forge wordcloud
conda install -c bokeh bokeh

Known issues

File encountered_issues.txt contains issues encountered during my work with tensorflow.