GSS0C24 / Scrape-ML

For new data generation Semi-supervised-sequence-learning-Project we have writtern a python script to fetch📊, data from the 💻, imdb website 🌐 and converted into txt files.

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IMDB Movie review Scrapping

Scrapping the movie review ✏️ using python programming language💻.

For new data generation Semi-supervised-sequence-learning-Project we have writtern a python script to fetch📊, data from the 💻, imdb website 🌐 and converted into txt files.

Introduction

Semi-supervised-sequence-learning-Project 💻 replication process is done over here and for further analysis creation of new data is required.

  • The following script includes the following.
  • Movie_review_imdb_scrapping.ipynb - Script to scrap the data from imdb website
  • rename_files.ipynb - Script to rename the scrapped text files as per the requirements
  • convert_texts_to_csv.ipynb - Python script to make a CSV file from the txt files for SVM processing

Dependencies

install Beautifulsoup using pip install beautifulsoup4

Installation

1️⃣ Fork the Semi-supervised-sequence-learning-Project/ repository
Follow these instructions on how to fork a repository

2️⃣ Cloning the repository
Once you have set up your fork of the /Semi-supervised-sequence-learning-Project repository, you'll want to clone it to your local machine. This is so you can make and test all of your personal edits before adding it to the master version of /Semi-supervised-sequence-learning-Project.

Navigate to the location on your computer where you want to host your code. Once in the appropriate folder, run the following command to clone the repository to your local machine.

git clone git@github.com:your-username/sanjay-kv/Semi-supervised-sequence-learning-Project.git.git

Final Dataset

1️⃣ Here is the Link to Final Dataset: Drive Link

About

For new data generation Semi-supervised-sequence-learning-Project we have writtern a python script to fetch📊, data from the 💻, imdb website 🌐 and converted into txt files.

License:MIT License


Languages

Language:Jupyter Notebook 96.5%Language:Python 3.5%