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Sentiment Analysis is the most common text classification tool that analyses an incoming message and tells whether the underlying sentiment is positive, negative our neutral. It's implemented using amazon reviews dataset in python using logistic regression.

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Sentiment-Analysis 😁

Sentiment Analysis is the most common text classification tool that analyses an incoming message and tells whether the underlying sentiment is positive, negative our neutral. It's implemented using amazon reviews dataset in python using logistic regression.

Tech Stacks 💻

Python 3.7

Prerequisites

  • You should install python version 3.7
  • import all modules required for the project

Modules used

  • pandas
  • numpy
  • matplotlib
  • seaborn
  • sklearn

Installation

Cloning this repository:

git clone https://github.com/Nishit014/Sentiment-Analysis.git

Install the required packages in your environment by using pip.

pip install -r requirements.txt

Usage

Open the project folder after installing requirements and run:

virtual_drums.py

Contributing

You are free to use this code for any purpose. If you have built anything interesting, contribute it back to this project. You could add more drums or improve the overall performance.

Note

Feel free to file a new issue with a respective title and description on the Virtual-Drums. If you already found a solution to your problem, I would love to review your pull request!

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Sentiment Analysis is the most common text classification tool that analyses an incoming message and tells whether the underlying sentiment is positive, negative our neutral. It's implemented using amazon reviews dataset in python using logistic regression.

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