Expense Tracker is a Python-based desktop application built with Tkinter and SQLite, designed for efficient expense management. It offers intuitive features for adding, categorizing, and analyzing expenses, making it ideal for personal or small business use.

Restaurant Orders é um sistema que visa melhorar a gestão de cardápios e estoque de um restaurante.

This project demonstrates basic data manipulation tasks using Python and Pandas. It covers CSV and JSON file handling, dataset analysis from Kaggle, filtering data, handling missing values, and importing/exporting Excel files.

🌟 Fraud Detection in Application 🌟 Through Isolation Forest and K-Means Clustering, the project detects suspicious patterns like inconsistent income, duplicate entries, and unrealistic employment data. This end-to-end workflow transforms raw data into actionable fraud insights — enhancing trust and accuracy.

Simple ASP.NET Core Web API for working with .csv files

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Dive into GitHub Web Scraping—an automated Python project using Requests and BeautifulSoup. Extract topic details and scrape top repositories effortlessly, storing data in CSV files for seamless analysis. Contribute and explore GitHub data efficiently. 🚀💻

X Clinic Program Application with a number of features with specified specifications and integrated with GUI.

Developed a comprehensive API using Node.js, Express, and MongoDB that allows administrators to manage user lists and send emails to subscribed users. This API features robust user authentication with JWT, user registration and login functionalities, list management capabilities, CSV file handling for batch operations, and custom email sending.

Travelling Salesman Problem (TSP) solution using several different methods.

🔍 Detect fraud in application data using machine learning and data visualization to uncover anomalies and enhance digital integrity.