spacy-nlp

NLP in Python with Deep Learning

Generating multiple choice questions from text using Machine Learning.

LanguageCrunch NLP server docker image

Train Spacy ner with custom dataset

Augmenty is an augmentation library based on spaCy for augmenting texts.

Excel Integration with spaCy. Training NER using Excel/XLSX from PDF, DOCX, PPT, PNG or JPG.

A Python library for detecting and filtering profanity

Python tutorials as Jupyter Notebooks for NLP, ML, AI

A resume filtering based on natural language processing

NLP Cheat Sheet, Python, spacy, LexNPL, NLTK, tokenization, stemming, sentence detection, named entity recognition

✒️ Language Tool style grammar handling with spaCy 2.0

Deep Learning notes and practical implementation with Tensorflow and keras. Text Analytics and practical application implementation with NLTK, Spacy and Gensim.

✨ 🧬 Turing AI - Semantic Navigation, Chatbot using Search Engine and Many NLP Vendors.

Full resources supporting the publication "A Pragmatic Guide to Geoparsing Evaluation."

Natural Language Processing using NLTK and Spacy

Repo containing the Twitter preprocessor module, developed by the AUTH OSWinds team

Collection of Notebooks for Natural Language Processing with PyTorch

Instructions for how to convert a BERT Tensorflow model to work with HuggingFace's pytorch-transformers, and spaCy. This walk-through uses DeepPavlov's RuBERT as example.

Interactive Jupyter Notebooks for learning materials

Keyword extraction with spaCy

🎲 KenLM extension for spaCy 2.0.

A visualization of Mahabharata - the Indian Epic. An analysis of the charachters Karna and Arjuna from the text; exploring their appearances, descriptions and associations in the epic.

Golang API for spaCy with Python gRPC

An end-to-end event extraction and summarization system.

NLP parser using NER and TDD

spaCy-wrap is a wrapper library for spaCy for including fine-tuned transformers from Huggingface in your spaCy pipeline allowing you to include existing fine-tuned models within your SpaCy workflow.

YouTube Transcript Summarization over Flask: This back-end uses Flask framework to receive API calls from the client and then respond with the summarized text response. This API can work only on those YouTube videos which has well-formatted closed captions in it. The same backend also hosts a web version of the Summarizer.