• I'm MLE :]

• I’m from Brazil

• 22 years

• Artificial Intelligence and Data Scientist Student at UFPB

• HCIA-AI Huawei Certificated;

• Machine Learning Engineering at Nubank

• Deployment of ML Batch or Online models
• Contributions on the Nubank ETL
• Make the integration of data providers into new versions of models

• Research about the state of the art
• Use deep learning and optimization techniques to maximize the production of the photovoltaic energy
• Embed the solution on Atlas200 DK

• Extraction of data from the database for cleaning and application of techniques
• Development of systems to do the process of extraction automatically
• Dashboards for Business presentations
• Finding insights from the data, by applying statistics techniques

• Huawei Artificial Intelligence Certification Course Monitoring
• Resolve student queries
• Weekly meetings to help resolve issues
• Helping teachers, individual reports for each student

• Research about the many areas in AI
• Share knowledge with more experience people in the AI area
• Develop hands-on projects about some area of AI

I was monitor of the Training Course for the HCIA AI Huawei 3.0 Certification during 6 months in 2021; I worked in a research project that involves the partnership between LASER and LAGID (CCSA) with the company MGITech and as AI Researcher of the project Huawei Solar Tracking Control (AI Based) in Embrappi and UFPB partnership project.

I am a research student at the Technology and Artificial Intelligence League (TAIL) in the UFPB and Data Science Intern at Nubank

• Automated narration for soccer games using computer vision This project was developed at TAIL (Technology and Artificial Intelligence League) in the Computer Vision directory. The methodology used was to first detect players, ball and goal using YOLOV5 and then detect the color of each team to distinguish them, with that, we can detect which team has the ball and when a goal happens, for example. All this was done only with computer vision, and no other information (only the name of the teams).

• Music Genre Prediction model, using RoBERTa This project was developed at TAIL (Technology and Artificial Intelligence League) in the NLP directory. The goal is to get a lyric as an input and get back the genre of that song. The methodology was: used the pre-trained model RoBERTa, fine-tunning the parameters with a dataset of lyrics and genres, and them deploy in HuggingFace repository. We get an 81% accuracy with a very tiny dataset (approximately 5000 instances), so we considered a good job.

• An Introduction to the Data Science world. A DataViz and Data Analisys project Every year kaggle does this competition were they give to us data about a research made with data scientists, so we made a jupyter notebook with some insight about all this data.

• A fan game of Pokemon, in C++ This is a simplicated version of the battles in Pokemon game. We use C++ and OPP to create all the logics and made a very fun game to play.

• A Introduction to the DataScience World This project was developed as a competition application for the data science website Kaggle. It analyzes, in narrative form, the profile of the data scientist in 2020, in addition to tips on how to start studies for the area, based on data. It was done in partnership.

• Olympics Games History: This was the final project of the introduction to data science course. This project analyse the history data of the Olympic games. The goal of the project was to present and analyze data from Olympic athletes in order to explore different dimensions of competition using variables such as: gender, nationality, performance, etc. At the end of the analysis, we hope to obtain coherent information capable of presenting something new to the reader.

• Implementing NumPy in C lang: This was the final project of the structured programming course. The goal of this project is to create an implementation for representation and manipulation of arrays inspired by NumPy.