Text Classification, Named Entity Recognition, and Transformers Overview Documentation

[UTSAVS26]

Closes: #79

• Title : Text Classification, Named Entity Recognition, and Transformers Overview Documentation
• Name: Utsav Singhal
• Identify yourself: SSOC'24 Contributor

Describe the add-ons or changes you've made 📃

Implemented a module for text classification to categorize text into predefined categories using machine learning algorithms. Developed a Named Entity Recognition (NER) feature to identify and categorize entities such as names, dates, and locations within text data. Additionally, created comprehensive documentation covering the concepts, applications, and implementation of Transformers in natural language processing (NLP).

Type of change ☑️

• New feature (non-breaking change which adds functionality)
• This change requires a documentation update

How Has This Been Tested? ⚙️

The text classification module was tested using a sample dataset to ensure accurate categorization. The NER feature was evaluated on various text samples to verify correct entity identification and categorization. Documentation was reviewed for completeness and accuracy.

Checklist: ☑️

• My code follows the Contributing Guidelines & Code of Conduct of this project.
• This PR does not contain plagiarized content.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• My changes generate no new warnings.

Note to reviewers 📄

The new features and documentation aim to enhance the project's NLP capabilities by providing essential tools for text classification and named entity recognition, along with a detailed overview of Transformers. Your feedback on these additions will be appreciated.

[github-actions]

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[UTSAVS26]

@Avdhesh-Varshney and @ArchitJ6 please review this pr.