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Classification model for measuring the accuracy of search algorithms used by e-commerce websites.

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ManviNagdev/Crowdflower_Search_Results

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Crowdflower_Search_Results

Crowdflower Search Results Relevance is a Kaggle Competition - https://www.kaggle.com/c/crowdflower-search-relevance/overview. The goal of this project is to create a machine learning model for measuring the relevance of search results. This model can be used to help eCommerce businesses to evaluate the performance of their search algorithms.

Dataset

The dataset is taken from https://www.kaggle.com/c/crowdflower-search-relevance/data.

Packages Required

  1. pandas==1.1.3
  2. tqdm==4.50.2
  3. nltk==3.5
  4. beautifulsoup4==4.9.3

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Classification model for measuring the accuracy of search algorithms used by e-commerce websites.

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