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Rafael Greca Vieira
Machine Learning Engineer and Data Scientist
Natural Language Processing, Python, MLOps, Deep Learning, and Machine Learning are among the topics that pique my interest. Also, I'm interested in working as a Machine Learning Engineer. Right now, I am studying about MLOps, Natural Language Processing, and PyTorch. In my spare time, I like to play (and watch) basketball and soccer, learn new languages (currently, I am improving my English and planning to learn Italian!), watch horror and thriller movies, and work on personal projects. Enjoy your stay!
Lastest Projects
Numbeo Scraper

Numbeo Scraper
NEW

In order to save time when searching for information about the quality of life in a particular country or city, the project's goal is to use web scraping frameworks (in this case, the BeautifulSoup4 library) to extract data from Numbeo's website.

Python Web Scraping GitHub Actions
End-to-end MLOps Project

End-to-end MLOps Project

The purpose of this project's design, development, and structure is to create an end-to-end Machine Learning Operations (MLOps) lifecycle to classify an individual's level of obesity based on their physical characteristics and eating habits.

Machine Learning MLOps Python Obesity Level Classification Multiclass Classification End-to-end
ScratchML

ScratchML

A Python library called ScratchML was created to build the most fundamental Machine Learning models from scratch (using only Numpy), emphasizing producing user-friendly, straightforward, and easy-to-use implementations for novices and enthusiasts.

Machine Learning Deep Learning Scratch Algorithms
MLflow with Natural Language Processing

MLflow with Natural Language Processing

In this project, we trained a Random Forest, XGBoost, and a BERT model to predict movies' genres based on their descriptions using an IMDb dataset hosted on Kaggle's website. Its main goal was to understand the applicability of the MLflow framework and how to use it to track different models during the training and evaluation steps, while also learning about the model's versioning and registry.

MLOps NLP MLflow Python Text Classification Machine Learning
Latest Posts
Image Processor Terraform Project

Image Processor Terraform Project
NEW

Development of an image processor workflow using AWS (S3, Lambda, and IAM Roles), Terraform, and Python. In this project, every image uploaded to an S3 bucket will be processed using a Lambda function written in Python, and then the processed image will be saved into another S3 bucket.
Lastest Publications

Unsupervised Clustering for Internal Combustion Engines Health Monitoring
NEW

We present an unsupervised machine learning approach designed to aid in the health monitoring of internal combustion engines, enabling the early detection of possible failures or degradation over time. Our methodology uses temporal data collected from a datalogger device connected to a vehicle's On-Board Diagnostics system. This data serves as input for a clustering machine learning model, which is trained incrementally over time to detect anomalies in multivariate time series. The decision-making process to categorize cluster behaviors as anomalies, which might be indicative of engine degradation over time, is based on several key metrics, such as the Jaccard similarity coefficient, relative cluster population, stability, and movement of the centroid over time. The proposed approach is validated on a public rotating machine dataset and tested on an internal combustion engine of a medium-sized vehicle in idle condition.

Machine Learning Engine Unsupervised Learning Clystering Internal Combustion