In this article, we will walk through three essential NLTK tricks to elevate your text preprocessing: preserving phrase integrity with the MWETokenizer, context-aware lemmatization with POS mapping, and statistical collocation extraction using association measures.
In this article, we will explore three essential spaCy tricks that every developer should have in their toolkit to maximize processing speed and customize entity recognition.
three essential spaCy tricks
selective pipeline loading, parallel batch processing, and hybrid rule-based statistical entity recognition
A deep dive into LiteParse's grid projection algorithm — how it extracts text from PDFs while preserving tables, columns, and alignment. Open source.
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization. - google/langextract
A guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools
A list of command-line tools for manipulating structured text data - dbohdan/structured-text-tools
Knowing the terminology is essential to understanding any tutorial.
Classifying cross-topic natural language texts based on their argumentative structure using deep learning
Case study of tweets from comments on Indonesia’s biggest media
Extract table from image with Nanonets table detection OCR. Learn OCR table Deep Learning methods to detect tables in images or PDF documents.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about Automatic Text Summarization and the various ways it is used.
This article will walk through an extractive text summarization process, using a simple word frequency approach, implemented in Python.
There is an unreasonable amount of information that can be extracted from what people publicly say on the internet. Learn how to do it.
This article discusses and compares different approaches of how to compare two text strings.
Quantized word vectors that take 8x-16x less space than regular word vectors - agnusmaximus/Word2Bits
Subtle changes to letter shapes can embed messages
LightTag, a newly launched startup from a former NLP researcher at Citi, has built a "text annotation platform" designed to assist data scientists who
Traditional strategies for taming unstructured, textual data
:zap: From finding text to search and replace, from sorting to beautifying text and more :art: - learnbyexample/Command-line-text-processing
A downloadable annotation tool for LLMs, NLP and computer vision tasks such as named entity recognition, text classification, object detection, image segmentation, evaluation and more.