/Amazon-Sentiment-Analysis

EDA on Amazon Data of a few million customers & then building a CNN Deep Learning Model.

Primary LanguageJupyter Notebook

Amazon Sentiment Analysis

 

Amazon Sentiment Analysis

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About   |   Features   |   Technologies   |   Requirements   |   Starting   |   Made By   |   Author


🎯 About

I have done Exploratory Data Analysis on the Data of a few Million Amazon Customer's Reviews & their Star Ratings in the Facebook's fastText format. I have done basic text processing & then built an unoptimized Deep Learning model on Convolutional Neural Network (CNN).

✨ Features

✔️ Uses Convolutional Neural Network (CNN)
✔️ Has 94.73% Accuracy
✔️ Uses Facebook's fastText for Fast Representation
✔️ DataSet Link:- www.kaggle.com/datasets/bittlingmayer/amazonreviews
✔️ Colab Notebook Link: https://colab.research.google.com/drive/1eaQXq_cg3RLqcDkhmeO4UntairnJdFbk?usp=sharing

🚀 Technologies

The following tools were used in this project:

✅ Requirements

Before starting, you need to have Git & basic Deep Learning libraries installed.

🏁 Starting

# Clone this project
$ git clone https://github.com/UtkarshPrajapati/Amazon-Sentiment-Analysis.git

# Access
$ cd Amazon-Sentiment-Analysis

# Install dependencies
$ pip install -r requirements.txt

# Run the project
$ jupyter nbconvert --execute Sentiment Analysis Amazon.ipynb

📝 Made By

Made with ❤️ by Utkarsh Prajapati

 

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