What all are the open source NLP tools available in web
There are numerous open-source Natural Language Processing (NLP) tools and libraries available on the web. Here's a list of some popular ones as of my knowledge. Please note that the landscape of open-source tools can change over time, so it's a good idea to check for the latest updates and releases:
1. **NLTK (Natural Language Toolkit)**: NLTK is a comprehensive library for NLP in Python. It provides easy-to-use interfaces for tasks like tokenization, stemming, tagging, parsing, and more.
2. **spaCy**: spaCy is another popular Python library for NLP. It's known for its fast and efficient processing and supports various languages. It offers pre-trained models for tasks like named entity recognition and part-of-speech tagging.
3. **Gensim**: Gensim is a library for topic modeling and document similarity analysis. It's widely used for tasks like word embedding (Word2Vec) and topic modeling (LDA).
4. **Stanford NLP**: The Stanford NLP toolkit provides a suite of NLP tools, including tokenization, part-of-speech tagging, named entity recognition, and dependency parsing.
5. **OpenNLP**: OpenNLP is an Apache project that offers machine learning-based tools for text analysis. It includes components like sentence splitting, tokenization, and named entity recognition.
6. **TextBlob**: TextBlob is a simplified NLP library built on top of NLTK and Pattern. It's user-friendly and great for basic NLP tasks like sentiment analysis and part-of-speech tagging.
7. **CoreNLP**: Stanford's CoreNLP provides a more robust set of NLP tools for deep linguistic analysis, including dependency parsing, sentiment analysis, and coreference resolution.
8. **fastText**: Developed by Facebook AI Research (FAIR), fastText is known for its efficient text classification and word representation capabilities. It supports many languages and is often used for text classification tasks.
9. **BERT (Bidirectional Encoder Representations from Transformers)**: Although BERT itself is a pre-trained model, there are open-source implementations and fine-tuning tools available for various NLP tasks, such as Hugging Face Transformers.
10. **Spacy-transformers**: This library extends spaCy to incorporate transformer-based models like BERT and GPT-2 for various NLP tasks.
11. **Tesseract**: Tesseract is an open-source OCR (Optical Character Recognition) engine developed by Google. It's used for extracting text from images and scanned documents.
12. **Flair**: Flair is an NLP library that focuses on state-of-the-art contextual word embeddings and provides easy-to-use APIs for various NLP tasks.
13. **AllenNLP**: Developed by the Allen Institute for AI, AllenNLP is a deep learning framework specifically designed for NLP research. It offers pre-built models and tools for text classification, semantic role labeling, and more.
14. **Transformers by Hugging Face**: Hugging Face's Transformers library provides a wide range of pre-trained models (including BERT, GPT-3, and more) and tools for various NLP tasks.
15. **Stanza**: Stanza is a Python NLP library by Stanford that provides pre-trained models for a variety of languages and tasks, including part-of-speech tagging, named entity recognition, and dependency parsing.
These tools cover a wide range of NLP tasks and cater to different levels of expertise, from beginner-friendly libraries to advanced research-focused frameworks. Depending on your specific NLP requirements, you can choose the tool that best suits your needs.