mouryaa Goto Github PK

airflow-s3toredshift-datapipeline

A pipeline using Airflow to move data from S3 to Redshift

analyzing-nycschools

Analyzing NYC High schools to look at factors that influence SAT scores such as demographics, class size as well as other attributes

aws-serveless-pipeline

A serverless pipeline using AWS Lambda and AWS Glue to unzip emails

college-major-earnings

Visualizing College earnings by majors

covid19-spread-analysis

A Flask app to look at Covid spreak

cyclos_secure

Senior design group at vcu

django_test

express-locallibrary

Local Library website written in node express

fandango-movie-inflation-analysis

Walt Hickey from FiveThirtyEight published a popular article where he presented strong evidence which suggest that Fandango's movie rating system was biased and dishonest. Fandango's officials replied that the biased rounding off was caused by a bug in their system rather than being intentional, and they promised to fix the bug as soon as possible. This project is to sample and analyze popular movies between two years, one before the fix and one after, to determine whether there is a difference in ratings.

hotelcaliforniathegame

Project for CS355 (Software Engineering) where we had to create a pacman like game

javascript-strings-lab-js-apply-000

knn-car-prediction

This project uses the KNN algorithm to create a model to predict prices of cars using the features in the dataset.

mta-analysis

Analysis of subway traffic gathered from the MTA website

predict-bike-rentals-random-forest

This project compares three different regression models to predict the number of bikes rented for a bike sharing system in Washington DC. The models used to predict include a linear regressor, decision tree regressor and a random forest regressor. Comparing all three models showed that the random forest had the least amount of error on prediction.

predict-home-prices-lin-regression

The following project takes housing data for the city of Ames, Iowa, United States from 2006 to 2010, to create a linear regression model to predict the house prices based on attributes in the dataset.

reddit-nlp

In this project, I used the Reddit API to extract the top 1000 posts for a whole year from the askreddit subreddit and applied some NLP techniques to analyze the data

redshift-etl-pipeline

This project creates a pipeline to load data into Redshift from S3.

spark-s3-datalake

Creates a data lake using spark from S3

to-do-list

Created a sample to-do list using JavaScript

twitter-sentiment-analysis-pipeline

The goal of this project was to build a real time streaming data pipeline to read tweets from Twitter.