Pinned Repositories
facebook_sentiment_analysis_token
analyze the sentiment of Facebook posts and visualize the results in a histogram. It connects to Facebook's Graph API to fetch posts, preprocesses the text, performs sentiment analysis, and displays a histogram of sentiment scores
landing-page-hospital
order-thali-octanet-task1
portfolio_done
Real-Time-Cyber-Incident-Monitoring-and-Analysis-Tool
This project is a Real-Time Cyber Incident Monitoring and Analysis Tool designed to collect, analyze, and visualize cyber incident data from various sources like social media platforms and news feeds. The tool leverages machine learning to classify and monitor incidents, providing real-time alerts and visualizations for cybersecurity teams.
Sentiment-Analysis
analysis application developed with Streamlit, designed to facilitate the evaluation of review sentiments—positive or negative—by leveraging a pre-trained machine learning model. Users can input review text and instantly receive sentiment predictions through a streamlined, interactive web interface powered by Streamlit .
Tech-Fest_Parampara-College
it is offical webpage for parampara event, to automate event, make easy to organise
TubeMetrics-Advanced-Analysis-for-YouTube-Channels
allows users to analyze YouTube channels by entering their handle. It fetches metrics such as subscriber count, view count, and engagement rates, integrates with Social Blade, and ranks channels based on predefined criteria.
twitter_sentiment_analysis
Classify tweets as positive or negative using the Naive Bayes classifier with NLTK. This project processes tweets from the `twitter_samples` dataset, extracts features, and trains a sentiment analysis model.
youtube_sentiment_analysis_API
analyzes sentiment in YouTube video comments using the YouTube Data API and a pre-trained model. It fetches comments, performs sentiment analysis, and visualizes the results on a web interface.
machphy's Repositories
machphy/Real-Time-Cyber-Incident-Monitoring-and-Analysis-Tool
This project is a Real-Time Cyber Incident Monitoring and Analysis Tool designed to collect, analyze, and visualize cyber incident data from various sources like social media platforms and news feeds. The tool leverages machine learning to classify and monitor incidents, providing real-time alerts and visualizations for cybersecurity teams.
machphy/landing-page-hospital
machphy/Tech-Fest_Parampara-College
it is offical webpage for parampara event, to automate event, make easy to organise
machphy/python_programming_
.py
machphy/portfolio_done
machphy/bday
machphy/Hand-Finger-detection-finger-Rajeev
machphy/twitter_sentiment_analysis
Classify tweets as positive or negative using the Naive Bayes classifier with NLTK. This project processes tweets from the `twitter_samples` dataset, extracts features, and trains a sentiment analysis model.
machphy/youtube_sentiment_analysis_API
analyzes sentiment in YouTube video comments using the YouTube Data API and a pre-trained model. It fetches comments, performs sentiment analysis, and visualizes the results on a web interface.
machphy/Bank-management-system
machphy/E-learning-web-page
machphy/facebook_sentiment_analysis_token
analyze the sentiment of Facebook posts and visualize the results in a histogram. It connects to Facebook's Graph API to fetch posts, preprocesses the text, performs sentiment analysis, and displays a histogram of sentiment scores
machphy/fb_sentiment_analysis
machphy/Hand_Gesture_Drawing
machphy/landing-page-vault
machphy/landing-page-watch-int
machphy/machphy
machphy/medical_diagnostics_for_particular
machphy/My-website
machphy/secondClass
I am creating every day notes of our javascript class, which is hosted on https://javascript.mrcool.in I am looking for someone in our class who help me to update it on daily basis
machphy/senti-analysis-flask
This project is a comprehensive sentiment analysis web application built with Flask. It allows users to input text and receive real-time predictions on whether the sentiment is positive or negative, based on a pre-trained machine learning model. app.py serves as the main Flask application, managing web routes and integrating the sentiment model.
machphy/Sentiment-Analysis
analysis application developed with Streamlit, designed to facilitate the evaluation of review sentiments—positive or negative—by leveraging a pre-trained machine learning model. Users can input review text and instantly receive sentiment predictions through a streamlined, interactive web interface powered by Streamlit .
machphy/TubeMetrics-Advanced-Analysis-for-YouTube-Channels
allows users to analyze YouTube channels by entering their handle. It fetches metrics such as subscriber count, view count, and engagement rates, integrates with Social Blade, and ranks channels based on predefined criteria.
machphy/Wether-web-intern
machphy/Youtube-clone
machphy/all-lab-pdf
machphy/CryptoToolkit
machphy/Javascript_fundamental_RT
machphy/malware_check
machphy/Parampra-Internal-paricipation-
..