Categorize the countries using ML algorithms (PCA dimension reduction and PAM clustering) with socio-economic and health factors that determine the overall development of the country. Then we can suggest the countries which HELP (international humanitarian Non-Governmental Organization) needs to focus on the most.

Personal repository for hobby and work projects

This is a dataset related to web logging with attributes such hit rate, visit date, exit rate, bounce rate, no. of imp. pages etc, A lot of Data Mining Technologies can be applied to extract better information out of it, I have applied clustering and classification and also created the report that is the model explanation is very important in te…

Machine Learning involves using historical data and predictive modeling techniques to forecast the future demand for cab rides and the corresponding supply of cabs needed to meet that demand. This can help transportation companies optimize their fleet management and improve customer satisfaction.

Production-ready ELT pipelines using Airflow

Performed Big Data Analysis on Bundesliga Football League Dataset using tools PySpark, spark-SQL, and numpy and done in Jupyter Notebook.

Ad-Hoc analysis on Consumer Goods data to retrieve required insights using My SQL.

Data-driven project aiding University of Leicester students in finding affordable housing through Python scraping, Excel analysis, and PowerPoint visualisation. Insights on rental prices, property types, and optimal locations.