Web Scraping program designed to examine the prices of items for sale on a Team Fortress 2 trading website (https://www.twine.net/signin then calculate the profit margin using the purchase prices listed on a second website (https://www.twine.net/signin The data is saved into a CSV file for later analysis in Microsoft Excel, allowing identification of items with a positive profit margin.

Using a fork of the TF2Autobot project (https://www.twine.net/signin and running 24/7 on a Linux machine, a “Trading Bot” was created and customized. This bot automatically posts buy and sell offers on the website https://www.twine.net/signin for items from the game Team Fortress 2, using the bot’s own Steam inventory. The result is an automated agent that generates passive income based on the profit margins of its transactions (monitored by the programmer). Additionally, the bot sends notifications via Discord for each transaction and maintains a history of profits and losses.

Development of a private server (non-profit) for the game Ragnarok Online, a classic MMORPG released in 2002. For educational and entertainment purposes, this server was emulated using rAthena, with C and SQL as the main programming languages (https://www.twine.net/signin The server was open worldwide for players to join.

Graphical interface developed in Python using the Tkinter and Pandas libraries a veterinary clinic in Rancagua, Chile. It allows for the registration and management of imported products from food and supply distributors (ID, Name, Purchase Price, Sale Price, Stock). The system automatically calculates the sale price for the customer and records all data in a CSV file in real time.

By using a dataset of electromyography (EMG) signals from athletes performing an acrobatic move in four different positions, a predictive Machine Learning model was developed. This model is capable of classifying the position in which the trained acrobatic move was performed when receiving a new EMG signal.

The purpose of this project was to create my Computer Science’s thesis that determines the most effective Machine Learning tool for analyzing these signals (Neural Networks, XGBoost, Logistic Regression, Random Forest, and SVM) by measuring Accuracy, Cross-Validation Accuracy, and calculating the ROC curve for each model to quantify their performance.