Helen Amin's Projects
Create an interactive dashboard to analyse Belly Button biodiversity dataset.
This is an insight into Jersey City Citi Bike growth rate, age/gender distribution and peak hours and busy stations at different time spans in 2020
Analysis of a game purchase data and Analysis of data of City schools all using Pandas
Climate Analysis for Honolulu,Hawaii for specific date range
A study of COVID-19 impact on unemployment in Australia
A Re-do of Perth City Properties project using Azure Data Engineering technologies such as Azure Data Factory (ADF), Azure Data Lake Storage Gen2, Azure Blob Storage, Azure Databricks.
End-To-End-Solution-DataEngineering-FinalProject
Data Engineer Bootcamp Project 2 - api.tvmaze.com
Produce Profit/Losses analysis ,produce election result from vote data ,Manipulate employee records format and Analysis of any such passage all using Python
Design and create an Employee Database based on some CSV files and analysis related to this data
ETL performed on used car and loan comparison site to show users different car loan options available.
Final Project - Summiting Everest
In this project, the goal is to find an optimized machine learning model to discover hidden planets outside of our solar system using Exoplanet Exploration dataset.
GeoJson Data for Australia
This project is about analyzing the current trends shaping people's lives by an interactive D3 chart
My personal repository
This will be the web version of the smoothie order form
Building a web application about Mars using information scraped from other websites
Create a map tool which can provide scientific data about natural hazards.
This project is about exploring and visualizing data of real estate properties in the City of Perth. It also includes property price range estimation using machine learning.
ELT Pipeline for Crypto data
Study on tumor volume treatment effectiveness using Pandas and Matplotlib
This project tries to describe the current state of home solar in Australia, as well as identifying areas of unmet potential and factors that may influence homeownerโs willingness to adopt this technology