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This is the machine learning project which uses sentimental analysis of amazon customer reviews.

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coderakib/Sentimental-analysis-of-amazon-customer-reviews

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Sentimental-Analysis-of-Amazon-Customer-Reviews

Application_1: Sentimental Analysis.

The Amazon dataset is available in .tsv file. The Amazon PC dataset is used for this application. Link: https://s3.amazonaws.com/amazon-reviews-pds/tsv/amazon_reviews_us_PC_v1_00.tsv.gz

The .tsv (Tab Separated Values) file was processed and cleaned using the code file named: 'data-cleaning.ipynb'.

After cleaning the data was converted to .csv (Comma Separated Values) file and transferred to RDBMS PostgreSQL server.

For the simplicity and avoid huge file size, a sample dataset named 'appl_1_amazon_pc.csv' has been created to perform Sentimental Analysis of reviews of Product Title 'Fire HD 7, 7" HD Display, Wi-Fi, 8 GB'

Execution:

  1. Launch the Jupyter Notebook either in your kernel or App.
  2. In the Notebook Dashboard navigate to find the notebook. Open it in your browser.
  3. Open the Jupyter Notebook file named: 'appl_1_sentiment_analysis.ipynb'.
  4. You can run the notebook step by step by pressing shift+enter.

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This is the machine learning project which uses sentimental analysis of amazon customer reviews.

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