Credit Scoring Model
- Neural Network
- Logistic Regression
Implementation of a probability evaluation system of default credits on the base of bank own data and the banking credit history over a given time.
Several types of classifiers have been implemented, including SVM and kNN, neural network, logistic regression and some others, as well as algorithms to select optimal parameters for the evaluation. The method of cross-validation was chosen to find the optimal parameters for each of them by taking risk assessment and expected profit into account.
The results were visualized.
The final solution was designed in the form of a program for a computer-aided decision-making.
- Data Classification
- Prediction Modeling
- Feature Selection
Model for restoring blurred and pixelated faces in a photo.
Workout helper app
Mobile app for the estimation of proper body positions during the workout.
Car rental price simulation and prediction
The goal of the project is to train models for car rental price prediction in Japan based on the prices and demand for car rental from some Japanese car rental companies and the history of weather data in Japan.