Just a little helper tool for proofreading my papers and such
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Updated
Aug 13, 2017 - Python
Just a little helper tool for proofreading my papers and such
Salesken Test for AI/ML Engineer
Zenify: Unveil the Mood of Words with Sentiment Analysis
Black Coffer Assignment
Text analysis, also known as text mining, is the process of automatically classifying and extracting meaningful information from unstructured text. It involves detecting and interpreting trends and patterns to obtain relevant insights from data in just seconds.
Analyze how people perceive plant-based diets online and generate marketing insights on the plant-based products.
Over 30,000 news about Myanmar which were published in 2021 were scrapped from the web and their titles were analyzed.
BookGPTs: Revolutionizing Book Interactions with AI. Create GPTs for any e-book, making technology accessible for all to engage in rich, AI-powered book discussions. No technical expertise required – upload a document and bring your favorite books to conversational life!
Media monitoring
A Text Analyzer library tool.
Final course project under the JHU data science course. This app uses a predictive text model built from the large corpus data. The model was built using the tidyverse package and n – gram function. The app was built using the Shiny package and it allows user to enter string and app will predict the next word.
Sentiment Analysis of Tweets for a renowned shoe brand
A toolkit for analyzing register, genre and style
"Detect sarcasm effortlessly! This Python app uses NLP and ML to analyze text sentiment, distinguishing sarcastic tones. With a user-friendly interface, input any text for real-time sarcasm identification. Achieve accurate results through advanced sentiment analysis techniques and trained models."
Natural Language Processing Based Text Analysis Project to detect Fake News that are being spread in Social Media
This project provides a simple script for determining the sentiment of a text input using TextBlob library in Python. It also returns the most positive and most negative sentence in the input text. The script can be used as a standalone tool or integrated into other projects.
This project implements a Named Entity Recognition (NER) system to identify and classify entities in text, such as PERSON, ORGANIZATION, and LOCATION. Utilizing machine learning and NLP techniques, it offers accurate extraction of meaningful information from unstructured data.
This repository is a hands-on exploration of essential NLP concepts, designed to build a strong foundation in text analysis. It offers practical exercises to understand how machines process and interpret human language.
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