A Static Analysis Tool for Detecting Security Vulnerabilities in Python Web Applications
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Updated
Dec 25, 2020 - Python
A Static Analysis Tool for Detecting Security Vulnerabilities in Python Web Applications
The ethical ad server - ads for developers without all the tracking
A digital clock application made with python and tkinter
All Basic to Advanced Algorithms
Dota 2 Match Result Predictor Telegram Bot Overview This project is a Telegram bot that leverages a XGBoost neural network model to predict the outcomes of Dota 2 matches. The bot provides users with real-time predictions based on current match data, making it a useful tool for Dota 2 enthusiasts and analysts.
About : Pdf2audio is web application which convert pdf to audio, pdf to text, pdf to image. for application development I use python programing language and it's backend web framework flask and some modules like pdf2image, pytesseract, PIL, gtts, tessereact-ocr .etc for front end I use html css bootstrap javascript and pwa(progressive web applic…
Sweetheart, an enchanting web experience, invites you to express affection with a simple question: "Will you date me?" Delight in the anticipation, as your crush responds with a heartfelt 'Yes' or a gentle 'No.' Capture the essence of romance in every interaction, making Sweetheart the perfect platform for genuine connections.
Python script that calculates Fleiss Kappa, a statistical measure of inter-rater agreement, on data from an Excel file.
Predict stock prices with an intuitive web app. Easy-to-use interface, accurate predictions.
a simple graphical user interface (GUI) application that interacts with the ChatGPT API. The application is built using Python and the Tkinter library. Users can input their questions, and the application will display the responses generated by the AI
Python library for recurring tasks in machine learning projects
Sentiment Analysis on Twitter Data . Classifying them based on polarity into positive, negative and neutral Using Classical Machine Learning methods.
Welcome to the repository of our garbage classification project! We have developed a model using PyTorch and EfficientNet-B4 that classifies garbage into twelve different types. The model has achieved an impressive accuracy of 98.45%.
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