This repository is a comprehensive, curated list of resources for learning about text mining and Natural Language Processing (NLP). It targets individuals seeking to understand or apply NLP techniques, offering a structured pathway through books, tools, datasets, and research papers. The primary benefit is providing a centralized, organized knowledge base for self-directed learning in this rapidly evolving field.

How It Works

The repository functions as a meta-resource, aggregating and categorizing links to external learning materials. It covers a broad spectrum of NLP topics, from foundational concepts like stemming and text cleaning to advanced areas such as transformers, language models, and knowledge graphs. The organization by topic and resource type (books, APIs, datasets, etc.) allows users to navigate the vast landscape of NLP efficiently.

Quick Start & Requirements

This is a curated list of links, not a software package. No installation or execution is required. Users can directly access the resources via the provided URLs.

Highlighted Details

• Extensive coverage of both R and Python ecosystems for text mining.
• Detailed sections on specific NLP tasks like sentiment analysis, document classification, and machine translation.
• Includes links to major NLP conferences, benchmarks, and popular datasets.
• Features resources on ethical considerations like bias in NLP.

Maintenance & Community

The repository is maintained by @stepthom. Contributions are welcome, with guidelines provided for submission.

Licensing & Compatibility

The creator has waived all copyright and related rights to this work, effectively placing it in the public domain. This allows for unrestricted use and adaptation.

Limitations & Caveats

As a curated list, the quality and availability of linked resources depend on external sources. The rapidly changing nature of NLP means some links or information may become outdated.