In this project, I develop a collaborative filtering recommender system for recommending movies, evaluate its performance and present the corresponding web app.

The EDA for the dataset providing data about www.airbnb.com users (Kaggle competition). Predicting, using XGBoost extreme gradient boosting algorithm, what five countries would be the most probable choice by a new user as a first booking destination.

Exploratory data analysis of the automobile data.

Clustering the profiles of teenagers based on their social activity. Segments are defined using k-means.

In this analysis, the system for predicting strength of concrete is developed using artificial neural networks.

Filtering mobile phone spam using the naive Bayes algorithm.

Predicting the frequency occurrence of several harmful algae in water samples. The models of multiple linear regression, regression trees and random forest are used for prediction.

Exploratory data analysis performed to answer the question: which chemical properties influence the quality of red wines? The regression model is provided, based on the analysis.

This document gives an overview of how to perform an exploratory data analysis with two variables in R.

This document gives an overview of how to perform an exploratory data analysis with many (more than two) variables in R.

This document gives an overview of how to perform an exploratory data analysis with one variable in R