One Benchmark Framework for Your Natural Language Processing Project

One Benchmark Framework for Your Natural Language Processing Project

In this article, I will show how to retrieve close to one million public text or PDF documents. Some of these documents are raw text, some are clean text, and some include categorical labelling. I will also introduce KILT, a benchmark framework for natural language models.

In this article, I will show how to retrieve close to one million public text or PDF documents. Some of these documents are raw text, some are clean text, and some include categorical labelling. I will also introduce *KILT, *abenchmark framework for natural language models.

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Thousands of PDF, Word, and Text Documents to Download for your NLP Project. Source: Unsplash

List of Lists of Public NLP Datasets.

The following are non-inclusive lists of lists of NLP datasets:

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  1. Awesome-Public-Datasets;
  2. Project Gutenberg: File Repository;
  3. Project Gutenberg: Top 100 EBooks as of 8/15/2020;
  4. Google Books API for Python;
  5. Google Books Ngram Viewer;
  6. Google datasets;
  7. textacy datasets;
  8. Kaggle datasets;
  9. fast.ai datasets;
  10. USC Machine Learning Repository datasets;
  11. pyquora: A Python module to fetch and parse data from Quora;
  12. Zillow: Real Estate and Mortgage Data;
  13. readthedocs.org;

machine-learning deep-learning dataset unsupervised-learning naturallanguageprocessing

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