final project of mathematical software 2 course at SBU

According to the CDC, heart disease is one of the leading causes of death for people of most races in the US. Our ML project leads to a better understanding of how we can predict heart disease.

This repository showcases my project completed during the Accenture North America Data Analytics and Visualization Virtual Internship. This project offered an immersive experience into the exciting world of data analytics and visualization with Accenture

The company hired you because they want to know what would be the 5 properties they should invest in and why, and which 5 you would not recommend investing in at all.

Accenture empowers you to be your best—personally and professionally. Every day around the world, we work with exceptional people, the latest and greatest tech and leading companies across industries. Deep dive into the evolving world of data from an analytics and visualization perspective.

Repository for EDA projects

News popularity prediction dataset analysis and modeling

EDA of Sephora sales data along with customer reviews using SQL and Excel as well as creating a Power point presentation for visuals, insights and recommendations

Project developed for the course Data Mining at UFSC

Data science Methodology

Data preparation: data understanding, heatmaps, data cleaning, dimensionality reduction

EDA for Chicago PD crimes form 2001 to 2023 (almost 8 million cases) using python, pandas and streamline dashboardes. Focusing on recurring trends and insights.

Анализ вакансий с сайта Headhunter

Completed a simulation focused on advising a hypothetical social media client as a Data Analyst at Accenture

some training, learning and TD/TP ressources

Final project for the course "Data Mining: Foundations" (Università di Pisa, LM Data Science and Business Informatics)

EDA for real estate data in the city of Connecticut from 2001 to 2020 using python, pandas and streamlit dashboards. Focusing on the shift in the housing market before and after 2008 financial crisis and the real estate boom in large neighboring cities.

In this project conducted in RStudio using the R programming language, we delved into Spotify data to unravel patterns and insights contributing to music's popularity. Employing statistical techniques and leveraging the power of ggplot2 for visualizations, our analysis aimed to provide a comprehensive understanding of what drives music preferences.

You have been hired by Walmart to survey the revenue of their stores in the USA and point out which store would be best to expand its size. It is necessary to analyze the weekly sales of each store, calculate some important information that will be asked, and at the end of it all, indicate which store should be invested in.

Vehicle insurance claim fraud detection dataset analysis and modeling