Gagandeep Saini's repositories
Amazon_Vine_Analysis
Big Data ETL using AWS RDS and PostgreSQL, and used PySpark to investigate whether Amazon Vine reviews are free of bias
Credit_Risk_Analysis
Identify credit card risk using Machine Learning algorithms
Election_Analysis
The purpose of this project was to do election data audit for a State election commission.This script can be used for any future election given the csv file would have relevant data. We just have to replace/add the name of candidates and counties in csv file
Fundraising_Campaign_Analysis
Performing analysis on past 4000 crowdfunding-projects to uncover the trend, so that an informed decision can be taken to launch a new successful fundraising campaign
Neural_Network_Charity_Analysis
The purpose of this project is to use deep-learning neural networks with the TensorFlow platform in Python, to analyze and classify the success of charitable donations.
NY-Citibike-with-Tableau
The purpose of this analysis was to demonstrate the usage of Citi Bike in NYC via visualization, so that it could help to convince investors that a bike-sharing program in Des Moines could be a solid proposal.
Pewlett-Hackard-Analysis
Employee database analysis on retiring employees using SQL and pgAdmin
Stock-Analysis
Green Energy stock Analysis for the year of 2017 and 2018 using VBA
Belly_Button
This project focuses on building an interactive dashboard to visualize the bacterial species living in the navel of candidates of a research about meat protein synthesis from human bacteria.
Cryptocurrencies
The purpose of this project is to use unsupervised machine learning to analyze a database of cryptocurrencies and create a report including the traded cryptocurrencies classified by group according to their features.
Election_Analysis1
brushing up the concepts
Mapping_Earthquakes
The objective of this project is to gather earthquake GeoJSON data from the USGS API, create and explore interactive maps of earthquakes around the world.
MechaCar_Statistical_Analysis
Testing whether or not the MechaCar has statistically significant differences in these metrics compared to competing models.
Mission_to_Mars
Using BeautifulSoup and Splinter to scrape full-resolution images of Mars’s hemispheres and the titles of those images, store the scraped data on a Mongo database, use a web application to display the data, and alter the design of the web app to accommodate these image
Movies-ETL
Within the scope of the Amazing Prime Hackathon, this project will create an automated pipeline that takes in new data, from Wikipedia data, Kaggle metadata and the MovieLens rating data. It then performs the appropriate transformations and loads the data into an existing PostgreSQL database.
PyBer_Analysis
Performing an exploratory analysis and creating visualizations using rideshare data to help improve access to rideshare services and determine affordability for underserved areas.
World-Weather-Analysis
The purpose of this project is to collect, analyze and visualize weather data across cities worldwide and to provide travelers with a tool that will allow them to determine their travel destination based on weather conditions.