Projects

Disease Prediction from Medical Data

In this project, we'll walk you through building a neural network model to predict the appropriate medication for patients based on their symptoms. We'll use a dataset containing patient symptoms and prescribed medications, preprocess the data, train a neural network, and make predictions based on new input symptoms.

Road Repair Cost Prediction

This project aims to predict the total cost of road repairs using a Linear Regression model. The process involves data preprocessing, training a machine learning model, evaluating its performance, and visualizing the results.

Crime Prediction and Prevention

This project aims to analyze and visualize crime data in Bucharest using geospatial mapping and machine learning techniques. The primary focus is on classifying crime severity and making predictions about crime severity using the K-Nearest Neighbors (KNN) algorithm. This comprehensive approach combines data processing, machine learning, and interactive visualization to provide valuable insights into crime patterns.

Traffic Management

This project demonstrates a complete workflow for building and evaluating a machine learning model (Random Forest Classifier) to predict traffic congestion in Bucharest based on various features such as weather conditions, road type, and traffic volume. It also includes visualization using folium to map traffic observations.

Predicting Future Interest Rates

In this project, we demonstrate a practical approach to forecasting interest rates using a Linear Regression model in Python. The goal is to analyze historical interest rate data, build a predictive model, and generate forecasts for future periods.