App Costa Dominicana
Costa Dominicana App is an innovative mobile application built with JavaScript, HTML, and CSS, packaged with PhoneGap to run smoothly on mobile devices. This app allows users to explore all the beaches of the Dominican Republic, offering a unique interactive experience with the option to view them in immersive 3D.
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App CRM
The implementation reinforced best practices in state management, dependency injection, and reusable components, as well as the effective handling of complex business workflows across multiple interconnected views. Special attention was given to performance optimization, code organization, and data consistency between modules such as customers, sales, orders, inventory, and warehouses.
Additionally, the project provided practical experience in designing a system prepared for future extensibility, cross-platform deployment, and integration with external services, highlighting the importance of clean architecture and well-defined application layers in modern frontend development.
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La Sierra
This is a web application built with Angular, designed as a dynamic and interactive platform. It includes advanced components such as image sliders, an integrated calendar system, and activity scheduling capabilities. The platform also allows users to register and manage locations they plan to visit.
Developing this project required implementing state-driven components, modular architecture, and efficient routing, which contributed significantly to expanding my expertise in frontend engineering and user-centered design. The system combines visual interactivity with practical features, resulting in a robust and intuitive application that demonstrates strong technical execution and thoughtful UX planning.
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Machine Learning ML5 and P5
This project is an interactive image and video classifier built using ML5.js and P5.js, designed to recognize and classify faces in real time using your own face as training data. It leverages the power of machine learning directly in the browser, without requiring any backend or external APIs.
The application captures video input from the webcam, processes each frame, and uses a pre-trained or custom-trained model to detect and classify facial images dynamically.
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