We've developed an intelligent real estate recommendation engine that achieves 95% accuracy in price predictions while personalizing property suggestions to individual preferences. By implementing the KNN algorithm, our system analyzes thousands of historical transactions to determine recommendation properties

This repository contains the "RFM Analysis" for a Sales Data of a Retailer in SQL. This is part of my Data Science Portfolio Projects

Using publicly available data for the national factors that impact supply and demand of homes in US, build a data science model to study the effect of these variables on home prices.

Breast cancer dataset analysis (UPM's Master in Data Science project for Data Process subject)

Descriptive analysis of trends in deaths

The Chinook Data Analysis Project leverages PostgreSQL, Python, and Google Spreadsheets to explore and analyze the Chinook music store database. Insights will be presented through Tableau Dashboards and Stories. Stay tuned for updates as the project evolves.

Implementing Python Machine learning to predict potential customers for a new launched product

Data Mining Web Application to Identify Anomalies in Public Procurement Rating Parameters

We've taken a Dataset of Automobile industry ad we're going to perform EDA (Exploratory Data Analysis). Also we'll apply a suitable Classifier, Regressor or Clusterer and calculate the accuracy of the model.

Using descriptive analysis to answer business questions and make recommendations to optimize Pizza Runner's operations and drive sales.

Covid 19 analysis using NYTimes dataset for USA country.

Exploratory Data Analysis on the fictional company, Cyclistic, a bike-share company out of Chicago. "R" was used to complete this analysis for the Google Data Analytics Professional Certification.

The present project aims to predict air pollution in Beijing, China, using the data set "Beijing Multi-Site Air-Quality Data Data Set"

Download and save and doing a descriptive analysis of Youtube's comments using python and Google API ( Youtube Data API V3 )

This repository consists of the jupyter notebook files of the first project I worked on. It has data processing, descriptive analysis and linear regression modeling to predict the total claim amount of the customers of an insurance company.

Descriptive analysis of trends in NHS 111 activity related to COVID-19

Using Pandas, Numpy, Seaborn, and Matplotlib

Linking a pre-existing R Project with GitHub. The project - Predicting Ice Cream Sales - was carried out on 'Statistics with R' module during the MSc Data Science for Business at the University of Stirling.

Descriptive text analysis of the words contained in the Dictionary of the Spanish language (DSL).

Exploring and predicting customers' churning from credit card service