Sentiment Analysis using Tensorflow and Spark

Sentiment Analysis, with spark as resilient data loader, and Tensorflow multiworker for distributed training

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Table of Contents

1. About The Project
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Contact

About The Project

Analysis is needed for reporting the customer feedback from a product, this project aim at analysis and report of customer insight,

Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Prerequisites

You need to install these dependency

• Python

• Kaggle Api

  Optional

  • Poetry

Installation

1. Clone the repo and get navigate to directory

   git clone git@github.com:henseljahja/sentiment-analysis-lstm-tensorflow.git

   then

   cd sentiment-analysis-lstm-tensorflow

2. Create virtual environment on terminal

   python3 venv -m ./sentiment_analysis/

   or

   python venv -m ./sentiment_analysis/

3. Activate the virtual environment

   source ./sentiment_analysis/bin/activate

4. Install packages from poetry

   poetry install

   or

   pip install -r requirements.txt

5. Get the data

   • Kindle Reviews dataset

   kaggle datasets download -d bharadwaj6/kindle-reviews

   • Glove dataset

   kaggle datasets download -d thanakomsn/glove6b300dtxt

Usage

Run the projects,

python3 main.py

and see the figure at /figures

License

Distributed under the MIT License. See LICENSE for more information.

Contact