The goal of this project is to track the expenses of Uber Rides and Uber Eats through data Engineering processes using technologies such as Apache Airflow, AWS Redshift and Power BI.
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Updated
Jun 29, 2022 - Jupyter Notebook
The goal of this project is to track the expenses of Uber Rides and Uber Eats through data Engineering processes using technologies such as Apache Airflow, AWS Redshift and Power BI.
A predictive model to help Uber drivers make more money
Analysis of Uber Data from NYC Open Data website
Uber web interface crawler / scraper - Convert the trips table into a CSV file
Exploratory and predictive data analysis with Uber's speeds dataset for London city.
EDA and data visualisation
Machine Learning Key Projects
This is the final data science project for USIT5609 MScIT Part II. Primarily made to learn Data Analytics, Machine Learning, and AI. To predict uber prices with external factors such as rain, temperature, time of day, day of the year, and more.
Code for fetching, sampling, and analysis of NYC taxi data from TLC and Uber for 2009-2018
Uber Data Analysis and Visualization using Python
Explore your activity on Uber with R: How to analyze and visualize your personal data history. Find out how you consume the Uber App using a copy of your data.
This is an analysis for the supply demand gap faced by the Uber and taxi companies
This app is integrated with UBER API. You can use uber features from your app.
Addressing some data science related issuesof a ride sharing app, Pathao
A machine learning project which predicts Uber trip data for different factors.
Uber and lyft data visualization, comparision and many analysis with python
Uber Traveling Time Analytics in DC Census Tract Zones
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