Using R Markdown for Data Analysis, Machine Learning

ETL and preprocessing of data to evaluate the possibilities of creating a machine learning models to predict whether a bidding item registered in purchases from ComprasGov systems will not have interested suppliers.

Build a predictive accident analysis app by loading historical accident data, preprocessing with Scikit-learn's Pipeline, training a model, and deploying using Streamlit for real-time predictions.

Introduction to Data Science: Term Project (2021W) - Predictive Analysis

Health Buddy is a web application that provides essential medical assistance, including predicting brain tumors, detecting retina problems, and finding nearby doctors. With a chatbot feature and AI-powered suggestions, it aims to improve the healthcare experience for users.

Predicting Next Booking Destinations for Airbnb Users. Feel free to access the Streamlit App in the link below.

Neste projeto de Análise de Recursos Humanos, temos como objetivo responder questões-chave sobre gestão de talentos e rotatividade de colaboradores em uma empresa fictícia.

"End-to-End Machine Learning Pipeline Creation Using DVC: A comprehensive MLOps solution on GitHub." This GitHub repository showcases the implementation of an end-to-end machine learning pipeline using DVC (Data Version Control) for efficient data management and MLOps practices. The pipeline covers the entire machine learning workflow.

This project implements a interface (form) using Flask to predict the classification based on inputed data, using a trained model.

Model klasyfikacyjny wykorzystujący algorytm Random Forest napisany w języku R.

This project aims to develop a robust classification model using test-takers' demographics and questionnaire responses from the ASD screening dataset to accurately identify individuals with Autistic Spectrum Disorder (ASD) through optimization of performance metrics.

Classification & Feature Selection for predicting blood glucose variability in Type 2 Diabetes

ML Classification Project

Class Project for Data Processing and Management(Monsoon'22)

This is the prediction system where i am using ML and Frontend Languages.

Employing several supervised algorithms to accurately model individuals' income using data collected from the 1994 U.S. Census to construct a model that accurately predicts whether an individual makes more than $50,000, This sort of task can arise in a non-profit setting, where organizations survive on donations.

In the project we built the following algorithms : Decision Tree Classifiier and Regressor, AdaBoost Classifiier , Gradient Boost Regressor

An ML algorithm to predict an individual's risk of adverse reaction to the COVID vaccine based on their medical profile.

Titanic dataset is very good dataset for beginners in machine learning. In This project we will find out which sort of people were likely to survive based on their features.