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The Machine learning project where user express there emotion and classify at the following (Sad, Joy, Love, Anger, Fear, Surprice).

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Emotional classification & Analysis

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About:

The Machine learning project where user express there emotion and classify at the following (Sad, Joy, Love, Anger, Fear, Surprice). We use a CNB model for text classification with the accuracy of 88%.

Data source:

Emotions

Notebook:

emotion-analysis-and-model

Emotion-Analysis

Note:

The prediction may encounter a unexpected expression result.

Installation:

Install this project on your local and here are the following steps.

1.) Open your terminal and clone the repo.

$ git clone https://github.com/nordszamora/Emotion-Expression

$ cd Emotion-Expression

2.) Install dependencies.

$ pip install -r requirements.txt

$ python nltk_setup.py

3.) Mysql database setup.

$ flask db init

$ flask db migrate -m 'emotion'

$ flask db upgrade

4.) Run project

$ python app.py

Unit test

$ cd tests

$ pytest

About

The Machine learning project where user express there emotion and classify at the following (Sad, Joy, Love, Anger, Fear, Surprice).

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