Alexandre R.

I have created an innovative machine learning tool in Python specifically designed for custom motion detection. Using TensorFlow, an industry-leading framework, I have developed a robust model capable of identifying and classifying complex movements with high accuracy.

The tool is trained with specific motion data, allowing for customization based on user needs. It utilizes advanced signal processing and data analysis techniques to extract relevant features from movements captured by sensors.

The main features of the project include:

- Model Training: Creation and fine-tuning of machine learning models using TensorFlow, optimized for accurate detection of specific movements.

- Signal Processing: Application of preprocessing techniques to improve the quality of input data, including filtering and normalization.

- User Interface: Development of an intuitive interface to facilitate the configuration and use of the tool by users.

- Performance Evaluation: Implementation of evaluation metrics to measure the accuracy and effectiveness of the model in real-time.

This project demonstrates my ability to apply advanced machine learning techniques and my experience in developing custom solutions using Python and TensorFlow.

I worked on the development of auth4art.com, an innovative online auction project specializing in artworks.

This project includes both frontend and backend, as well as the integration of blockchain technology to ensure security and transparency in transactions.

Using Vue.js, I developed an intuitive and attractive user interface that provides a smooth and enjoyable user experience.

The backend was built with PHP Laravel, ensuring a solid and scalable structure for managing users, auctions, and transactions.

I developed a robust API in PHP Laravel that facilitates communication between the frontend and backend, ensuring that all auction operations are carried out efficiently and securely.

To ensure the authenticity and security of transactions, blockchain technology has been implemented with Node.js code.

This allows each transaction to be recorded immutably, providing an additional layer of trust and transparency for users.

The entire project is deployed on Amazon Web Services (AWS), leveraging its scalability and high availability capabilities. This ensures that auth4art.com can handle a large volume of users and transactions without compromising performance.

auth4art.com represents a complete and secure solution for online art auctions, combining cutting-edge technologies to offer a reliable and efficient platform.

For this project, we used a range of modern and robust technologies.

The backend was built with Laravel (versions 5.5 to 9), ensuring a solid and scalable foundation for the application. On the frontend, we used Vue.JS and React.JS to create a dynamic and responsive user interface.

The database is managed by MySQL, with stored procedures to optimize the performance of complex queries.

We also integrated SASS for style management, ensuring a consistent and maintainable design.

Finally, REST APIs were implemented to allow fluid communication between the different parts of the application and with external services.