Sources for some videos
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Updated
Mar 31, 2019 - Jupyter Notebook
Sources for some videos
To identify the root cause of cancellation and non-availability of cars addressing the Uber supply-demand gap.
In this Project i will do analysis on Uber data, will use some library which are mentioned below
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 app is integrated with UBER API. You can use uber features from your app.
A machine learning project which predicts Uber trip data for different factors.
This is an analysis for the supply demand gap faced by the Uber and taxi companies
Addressing some data science related issuesof a ride sharing app, Pathao
Uber and lyft data visualization, comparision and many analysis with python
Uber Traveling Time Analytics in DC Census Tract Zones
Code for fetching, sampling, and analysis of NYC taxi data from TLC and Uber for 2009-2018
Uber Data Analysis and Visualization using Python
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.
Machine Learning Key Projects
EDA and data visualisation
Exploratory and predictive data analysis with Uber's speeds dataset for London city.
Uber web interface crawler / scraper - Convert the trips table into a CSV file
Analysis of Uber Data from NYC Open Data website
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