🚀 Explore Gradient Boosting techniques and low-default modeling for financial data science, enhancing strategies for tackling extreme class imbalance.

✯ Empowering businesses with AI-driven technologies like Copilots, Agents, Bots, and Predictions, alongside intelligent Decision-Making Suppor

🧠 Hands-on AI & ML guide: from tensors to neural networks, with code, formulas, and model evaluation.

🛢️ NoSQL: Building Databases in Practice (Not Only SQL)

⚡️ Final extension project by the Center for Data Science and Artificial Intelligence at PUC-SP. This initiative applies AI, IoT, and data-driven strategies to optimize water and energy systems in the Smart City Laguna (Fortaleza, Brazil), in collaboration with Proptech, Planet Smart City, UN-Habitat and Starlink. 💦

SumBot Free Code - AI-Powered Message Summarization ChatBot

🏆 HackaPUCSP 2024 - - Data Science and AI Hackathon - Pontifical Catholic University of São Paulo

🎭 Storyteling for Data Science and Artificial Intelligence - PUC-SP University

📊 An analysis of voting patterns in São Paulo's 2024 elections, focusing on voter behavior, absenteeism, and geographic trends.

💎 Diamond Valuation Prediction

𓁟 THQTH - Awakening Game - It's a guessing game, where the program chooses a random number and the player tries to get it right. 🧬

🪐 2-Gradient Boosting Machines and Low-Default Modeling: A repository for research, implementation, and best practices with Gradient Boosting methods (GBM, XGBoost, LightGBM), H2O AutoML, and robust strategies for modeling extreme class imbalance ("Low Default") in data science for finance and risk.

🌻 This repository offers guidance on recognizing, preventing, and addressing workplace gaslighting. It helps organizations, teams, HR professionals, psychologists, and students stay healthy, resilient, and psychologically safe, combining psychology, humanistic AI, and ethics. 🌱

💳 This repository focuses on building a predictive model to assess the likelihood of credit card defaults. The project includes data analysis, feature engineering, and machine learning to provide accurate default predictions.

🎬💰 Analyze movie companies' revenue, release strategies, and financial performance using statistical techniques for actionable insights. This project explores data on total revenue, number of releases, and lifetime gross to uncover patterns that can drive strategic decisions in the film industry.

Web Scrpping - Beautfull Soap and Selenium

Predict which passengers are transported to an alternate dimension

This repository is dedicated to studying how we can prevent customers from switching to other telecommunications services, a practice commonly referred to as "churn".

🤖 AI Chatbots with IBM Watson Assistant