TopicModeling | repository contains scripts to train Topic Models | Topic Modeling library

by Rochan-A Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | TopicModeling Summary

TopicModeling is a Python library typically used in Artificial Intelligence, Topic Modeling applications. TopicModeling has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However TopicModeling build file is not available. You can download it from GitHub.

This repository contains scripts to train Topic Models on Hotel Reviews. This work is done under the guidance of @Anupam Mediratta as an Intern.

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Quality

Security

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Support

TopicModeling has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

TopicModeling has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of TopicModeling is current.

Quality

TopicModeling has 0 bugs and 0 code smells.

Security

TopicModeling has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

TopicModeling code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

TopicModeling is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

TopicModeling releases are not available. You will need to build from source code and install.

TopicModeling has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed TopicModeling and discovered the below as its top functions. This is intended to give you an instant insight into TopicModeling implemented functionality, and help decide if they suit your requirements.

Construct a matrix of the topic frequencies .
Force unicode to unicode .
Process a set of text .
Compute the word weight probability for each topic .
Fit a partial embedding .
Compute the list of coherence values .
Normalize the weight matrix .
Return a list of the words in the file .
Sort a matrix .
Preprocess sentences .

Get all kandi verified functions for this library.

TopicModeling Key Features

No Key Features are available at this moment for TopicModeling.

TopicModeling Examples and Code Snippets

No Code Snippets are available at this moment for TopicModeling.

Community Discussions

Vulnerabilities

No vulnerabilities reported

Install TopicModeling

You can download it from GitHub.
You can use TopicModeling like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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