Exploring the history of word usage in English texts with a weighted popularity history plot.
-
Updated
Sep 14, 2024 - Java
Exploring the history of word usage in English texts with a weighted popularity history plot.
Model Generator for Firestore
A simple Rock-Paper-Scissors game using an N-Gram AI to detect player patterns
A robust method integrating N-gram encoding and ensemble modeling for enhanced splice site prediction accuracy.
Sentiment Analysis of Twitter Data (saotd)
Generate Elon Tweets, McDonald's Reviews and Airline Reviews
This repository contains an implementation of N-Gram Language Models (unigram, bigram, and trigram) and a Beam Search Decoder for correcting text with random errors. The code is written in Python and utilizes the NLTK library for natural language processing tasks.
Using k-nearest neighbors, and infinite-lookback ngrams with LLMs
Este proyecto de Minería de datos consiste en obtener N-Gramas y poder clasificar la información de un conjunto de datos de Netflix preestablecidos, dando como resultado una minería de textos y representado esta información con gráficos
Simple tool for training n-gram language model
This analysis uses ConsumerAffairs reviews to uncover reasons behind 1-star Starbucks ratings in the US. It uses a text analysis to identify service, product, and cleanliness issues impacting customer satisfaction.
Haiku-Search is a high-performance fuzzy search library designed for web applications. It is built using Rust and compiled to WebAssembly
Concepts related to NLP summarized with mathematical intution.
Machine learning based text classification in JavaScript using n-grams and cosine similarity
Character-level n-gram models from scratch
Recovery of ActiveWatch statistical text analysis from 20th Century Java code saved on a CD-ROM disk. This probably should be rewritten, but can now demonstrate AW mapping of dynamic text content and detection of unusual activity.
Finding insights on what could be improved at a restaurant based on reviews. Project contains the implementation, dataset and a written report. Methods utilized include LDA, NER, keyword extraction, length analysis, association rules mining, N-gram analysis and more.
Add a description, image, and links to the n-grams topic page so that developers can more easily learn about it.
To associate your repository with the n-grams topic, visit your repo's landing page and select "manage topics."