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Project: NLP Preprocessing Pipeline

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Description

In this project, you will create a reusable pipeline for preprocessing text data for NLP tasks. This project will help you understand how to standardize text data preprocessing to improve the efficiency and accuracy of NLP models.

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Project Prompt

  • Develop a pipeline that performs common NLP preprocessing tasks such as tokenization, stopword removal, and stemming.
  • Implement features for customizing the preprocessing steps based on the specific needs of different NLP tasks.
  • Create a user-friendly interface for configuring and running the pipeline.
  • Ensure the pipeline is modular and reusable across various NLP projects.

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Getting Started

  1. Choose suitable NLP libraries for text preprocessing (e.g., NLTK, SpaCy).
  2. Set up a backend service to handle text preprocessing tasks.
  3. Develop the frontend interface for configuring and running the pipeline.
  4. Implement features for customizing and reusing the pipeline across different projects.
  5. Test the pipeline with various text datasets to ensure flexibility and effectiveness.

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Deliverable

A reusable NLP preprocessing pipeline with a user-friendly interface for configuring and running text preprocessing tasks, ensuring modularity and reusability across different NLP projects.