Simple Summarizer using python
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Updated
May 21, 2024 - HTML
Simple Summarizer using python
Personal machine learning projects. (jupyter notebooks, python scripts, KNIME, SQL, scrapers etc, & R for Structural Equation Modelling on UX/CSat)
Analyze the sentiment in the comment section of YouTube.
Rating: (8/10): ThematicBot is an AI-based chatbot developed using TensorFlow, spaCy, and KMeans clustering to generate contextually appropriate responses, improving user experience through tokenization, embedding, and Tkinter library management.
Telegram bot for translation messages to certain languages
The objective of this assignment is to extract textual data articles from the URL and perform text analysis to compute variables.
The Sentiment Analysis App, built with tkinter and TextBlob, features a main window with a violet background. Users input text in a provided box, clicking "Analyze Sentiment" triggers analysis. The app checks for empty input, displays results (Positive, Neutral, Negative) in a label below. Continuous event handling keeps the app responsive.
The global supply chain is a crucial driver of the world economy, enabling the movement of goods and services worldwide and directly impacting economic growth. Analyzing sentiment surrounding the global supply chain in March 2024 reveals whether it's positive or negative, offering insights into improvements and disruptions.
This is a sentiment analysis project based on pretrained modules like TextBlob and VADER on Amazon_Food_Reviews dataset.
Script designed to perform sentiment analysis on news articles retrieved from the NewsAPI based on a user-defined keyword.
Sentiment Analysis of Amazon Food Reviews to the customer ratings using VADER, TextBlob and Flair
A simple Python Program to Analyze Sentiments using TextBlob Python Library.
This represents the final capstone project in my HyperionDev Data Science (fundamentals) course. A dataset of Amazon customer reviews is analysed using natural language processing.
Uses streaming twitter data based on custom keyword to generate the sentiment of users around that keyword using TextBlob.
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