tripleten

Share your photos, anyone can like them. Only you can delete them.

Evaluación académica del Sprint 2 del bootcamp TripleTen. Limpieza y análisis básico de datos de usuarios/as usando condicionales, bucles, listas y validación de errores

TripleTen Data Science Professional Training Program projects.

This is a demo created for online session practice for Tripleten cohort

Make.com automation that classifies customer feedback sentiment with Google Gemini AI and logs structured results to Google Sheets.

Foundational Python projects covering data cleaning, data processing, control flow, and introductory data analysis.

Aplicación Full Stack interactiva desarrollada como proyecto final en Tripleten. Implementa lógica avanzada con TypeScript, arquitectura modular (Client/Server) y despliegue con Docker.

Interactive dashboard analyzing car listing data using SQL and visualization tools.

The library: a web project to solidify CSS styling using the BEM framework.

Intermediate Python exercises and projects completed during the TripleTen Data Analytics Bootcamp, covering dictionaries, functions, Pandas, and data preprocessing.

Statistical data analysis using descriptive statistics, probability theory, hypothesis testing, and business decision-making with Python.

A project finished 04-02-2026 as part of the TripleTen Data Science program using real-world data and mimicking real-world project requirements. Task was to train a machine learning model for use on the Rusty Bargain app to estimate a car's market value on demand. Lowest RMSE was 1710.25, and that model delivered predictions in 207 milliseconds.

Portfolio of TripleTen Data Science projects covering Python, SQL, visualization, and machine learning.

A project finished 04-09-2026 as part of the TripleTen Data Science program using real-world data and mimicking real-world project requirements. Task was to analyze time series data and use machine learning to predict future hourly taxi order rates for Sweet Lift Taxi. Lowest RMSE was 41.16 using a SARIMA model.

A RAG-powered knowledge assistant built with ChromaDB and Sentence Transformers that answers Machine Learning questions with confidence-based response handling and source attribution.

Software development tools, Git, GitHub, version control, and web application deployment using Render.

Projeto do Sprint 5 - Implementar um Dashboard de aplicativo Web no Render

Sitio web de biblioteca desarrollado con HTML y CSS, enfocado en estructura semántica, diseño limpio y maquetación responsiva.