Hello there! 👋 I'm currently involved in a variety of Machine Learning/AI projects across Europe as part of the skilled team at Capgemini Denmark. With a background in Applied Economics and a Master's from the Technical University of Denmark, my expertise lies in Machine Learning Engineering and AI in Cloud, particularly with AWS and Azure. My key areas of focus encompass closed-loop systems (MLOps), cloud architecture, and knowledge-sharing through teaching sessions. Welcome to my portfolio, and glad to connect!
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Hello there! I am a 25-year-old Brazilian living in Denmark. I am working as a Machine Learning Engineer, where I build and teach data tools to help businesses make informed decisions. I specialize in MLOps, and Cloud architecture enabling organizations to leverage data to its fullest potential.
Outside of work, I am involved in a personal project that helps Brazilian students study abroad, something that resonates with me as I believe in giving back to society. I collaborate with an NGO called BRASA to achieve this goal.
About MeWith over 5 years of experience working with clients from around the globe, I specialize in designing and developing data projects that enable businesses to achieve their targets. My work encompasses everything from data exploration to machine learning, with the ultimate goal of helping organizations gain deeper insights and make better decisions.
Linkedin Download My ResumeThis project explores long-form question answering using a BART and sparse-retriever stack to generate detailed answers from Reddit questions, using information from Wikipedia. Three models were fine-tuned for AskScience, AskHistorians, and Eli5 subreddits respectively. While each model performed better on its corresponding subreddit, the Eli5 model achieved higher ROUGE-2 score on AskScience and provided relevant answers to both specialized subreddits, highlighting the potential of Deep Learning for long-form QA.
Case StudyThis project aims to tackle the challenge of handling large amounts of data from AirBnB using PySpark, a powerful big data processing framework built on top of Python. With the exponential growth of AirBnB's data, traditional data processing methods have become inefficient and ineffective. In this project, we will leverage PySpark to efficiently process and analyze AirBnB's massive data sets, enabling us to extract valuable insights and make data-driven decisions. By combining the power of PySpark and Python, we can create a scalable and cost-effective solution for AirBnB's big data challenges. This project will provide a valuable case study for anyone looking to leverage PySpark for efficient big data processing.
Case StudyThis project explores the effectiveness of ARIMA models with seasonality for time series forecasting and validates its performance through residual analysis. The findings will be useful for anyone interested in using ARIMA with seasonality for forecasting time series data.
Case StudyThis project builds a movie recommendation system using Python and TMDB. The system utilizes collaborative filtering techniques to generate personalized movie recommendations for users based on their viewing history.
Case StudyThis project aims to analyze crime patterns in the San Francisco area using Python. By exploring the public dataset provided by the San Francisco Police Department, we can identify patterns and trends in criminal activity and visualize the data using various techniques such as heatmaps and time series analysis.
Case StudyThe aim of this project is to investigate the potential link between water quality and real estate values in different areas of New York City using Python and Alteryx. By analyzing publicly available water quality data and real estate values, we can identify potential patterns of inequality and prioritize common problems based on their impact on different areas.
Case StudyThis project aims to investigate the potential risk of bird strikes on airplanes in the United States by creating an interactive dashboard using Tableau. By analyzing publicly available data on bird damages to airplanes, we can visualize the frequency and severity of incidents across different types of aircraft and locations.
Case StudyAlexandre is an extremely committed and productive team player. He finds satisfaction in contributing to teams and individuals, and for this reason has become a fundamental part of our team. He is especially talented in projects that require analysis and constant learning. Being a futurist, he is always looking for improvements and new challenges, which inspires and encourages his colleagues to also deliver beyond the expected standard.
During the last year at university, we spent plenty of time working together on our bachelor thesis. Despite already working full-time, Alexandre was always there, eager to help and showing full commitment to our research, he never gave excuses for not doing his part. Faced with similar situations, many people follow the principle of least effort, but not Alexandre. He is one of the most ambitious and dedicated person I have ever met, and I wish him all the best for the future!
have had the pleasure of knowing and working with Alexandre for three years, he brings energy, enthusiasm and commitment to every project he is assigned to. These traits are expected in any successful member of a business organization, and in this regard, Alexandre fits right in. It consists of providing high quality decision-making solutions, which speaks volumes to his overall intellect and ability to learn new things in order to achieve his goals.