My works

• RAG with Hugging Face Model:

  This project implements a Retrieval-Augmented Generation (RAG) pipeline using Hugging Face models, ingesting local documents (PDF/TXT/MD/CSV), creating embeddings for semantic search, retrieving the most relevant chunks, and generating grounded answers via CLI or a FastAPI endpoint.

• LangChain and YouTube:

  This project extracts a YouTube video's transcript, summarizes it using Google's Gemini model via Langchain, and displays it all in a Streamlit application.

• Churn Prediction:

  The goal is to build a model with predictive power and provide insights into the behavior of customer churn for the company.

• Airbnb Toronto Data Analysis:

  This notebook looks at neighbourhoods seperated into clusters and what features of am AirBnb listing determines the price per night and how many bookings they get.

• Human Resource Analytics:

  Data app used to display the Machine Learning solution to the Human Resource Analytics problem.

• Credit Card Fraud Detection:

  This notebook looks to perform comparative analysis of Credit Card Fraudulent detection by using machine learning techniques, as logistic regression, KNN, Random Forest and SVM.

• Covid19:

  Coronavirus (COVID-19) disease situation dashboard with latest data in the BRAZIL (08/08/2021)

• Covid panorama in Brazil:

  COVID-19 disease situation storytelling with latest data in the BRAZIL (07/03/2022)

• Suicide:

  Yellow September (World (1985-2015))

• Stroke:

  Analyzing and Modeling Stroke Data.

• Flask-SQLAlchemy and CRUD with MySQL:

  Flask-SQLAlchemy is an extension for Flask that adds support for SQLAlchemy to your application. It aims to simplify using SQLAlchemy with Flask by providing useful defaults and extra helpers that make it easier to accomplish common tasks.