Prediction of Credit Card Default
This project focuses on developing a data analytics product and predictive tool to manage risks associated with extending consumer credit.
Welcome to my project portfolio. Here you will find a collection of works I have completed. Primarily, projects related to artificial intelligence, computational analytics, and cloud computing. I worked with languages such as SQL, Python, and HTML5. Additionally, I used technologies like Docker, React Native, and various AWS tools to develop scalable, efficient, and robust solutions. All solutions are focused on addressing challenges within the Colombian industry (healthcare, banking, finance, and education) and for me to learn new computational skills. Each project includes a detailed description and links to code repositories and additional documentation.
This project focuses on developing a data analytics product and predictive tool to manage risks associated with extending consumer credit.
Analytic product focused on the results of the Saber 11 tests for pre-college students in Colombia. Tailored for principals and administrators of public and private schools interested in understanding the factors affecting student performance and predict grades in the Saber 11 tests.
This app leverages Vonage for emergency notifications, Firebase for user authentication, and python with Flask for the backend. It employs the Transformers library and sentiment_analysis_spanish for AI-driven mood analysis. The frontend is built using React Native and Expo.
A comprehensive explanaition of my progressing from basic to advanced levels in Tableau, where I learned to connect, transform, and visualize data. Additionally, I have deepened my expertise with Microsofts suite of analysis tools, including Excel, Power Query, Power Pivot, and Power BI.
This webpage allows users to interact with a stock portfolio by buying and selling shares. It displays the performance of portfolio stocks with charts and technical analysis. Additionally, also incorporates a neural network model for stock price predictions
Here, I explore key topics like data governance, business intelligence, and emerging trends such as IoT, Big Data, and Data Lakes. I've also applied my knowledge in a hands-on project, developing a restaurant management system using SQL, PHP, and MySQL, with a focus on data security.
I completed a Prompt Engineering course focused on techniques like summarizing, inferring, and transforming text with large language models. I applied this knowledge to develop a specialized ChatGPT for real estate marketing, optimizing SEO, generating A/B test variants, crafting targeted content, and evaluating property prices for sales and rentals in Colombia.
AI chatbot designed to answer questions about sexual health, focused on regulations and health entities in Colombia.
Welcome to my language learning journey! Ao longo dos anos, mergulhei nos fascinantes mundos do inglês, francês e português através de diversos cursos, viagens e projetos pessoais. De suivre des cours spécialisés en langues à voyager à travers les pays et créer des livres de recettes uniques en portugais.
Developed a machine learning system to predict patient hospital stay times in emergency units using data from 55 IPS in Medellín. The CatBoost model achieved the best accuracy (MAE: 8.875 hours) and powers an interactive web tool for quick, reliable predictions and visual insights.
Built a machine learning model to perform sentiment analysis on Yelp reviews. A subset of 70,000 reviews was preprocessed using lemmatization and stopword removal, then tokenized and padded for input into a Bidirectional LSTM model. The model achieved reliable predictions with metrics like accuracy, confusion matrix, and ROC curve.