24 skills found
DavieObi / Dynamic Pricing Model Developed a dynamic pricing model for a ride-sharing service to optimize fares in real-time. Conducted data analysis, engineered supply-demand features, implemented a rule-based strategy, and built a Random Forest model. Achieved high prediction accuracy and increased profitability while maintaining customer satisfaction.
cnbird1999 / Realtime Traffic DetectionVideo surveillance units are usually the first element of a security system. While they are the most intuitive to understand and can be programmed for many tasks, they also have many vulnerabilities, such as sensitivity to light levels and large computational requirements. The article presents an application of computer vision methods to traffic flow monitoring and road traffic analysis. The application is utilizing image-processing methods using OpenCV library designed and modified to the needs of road traffic analysis. This method gives functional capabilities of the system to monitor the road, to initiate automated vehicle tracking, to measure the average speed. This system is based on stationary video cameras and an onboard arm processor running on android or linux processing the video and sending the processed data to a central server connected to wide area network or through GPRS. This software was made to save users time so that they don’t get stuck in traffic jams and avoid them beforehand as they have prior knowledge about the traffic conditions on the alternate routes, so that users could choose the route with least traffic and hence shall reach his/her destination hassle free. What users need to do is, subscribe to the routes (from their android phone) in a particular area, our software will tell the user about the traffic density in each of the alternate routes available in that area and suggest the best route with least traffic to the user. Therefore by using our software from any android device, the user will enjoy a hassle free ride towards his destination.
tianqizzz / Uber Rider Churn AnalysisUber is interested in predicting rider retention. To help explore this question, they have provided a sample dataset of a cohort of users.
BGRicker / GitallicaRide the Lightning by performing temporal diff analysis of distributed version control logs ⚡️
Devtown-India / HandsOn Data Analysis And MLOver the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent bicycles on a very short-term basis for a price. This allows people to borrow a bike from point A and return it at point B, though they can also return it to the same location if they'd like to just go for a ride. Regardless, each bike can serve several users per day. Thanks to the rise in information technologies, it is easy for a user of the system to access a dock within the system to unlock or return bicycles. These technologies also provide a wealth of data that can be used to explore how these bike-sharing systems are used. In this project, you will use data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. You will compare the system usage between three large cities: Chicago, New York City, and Washington, DC. Day:1 In this project, Students will make use of Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. You will write code to import the data and answer interesting questions about it by computing descriptive statistics. They will also write a script that takes in raw input to create an interactive experience in the terminal to present these statistics. Technologies that will be covered are Numpy, Pandas, Matplotlib, Seaborn, Jupyter notebook. We will be giving the students a deep dive into the Data Analytical process Day:2 We will be giving the students an insight into one of the major fields of Machine Learning ie. Time Series forcasting we will be taking them through the relevant theory and make them understand of the importance and different techniques that are available to deal with it. After that we will be working hands on the bike share data set implementing different algorithms and understanding them to the core We aim to provide students an insight into what exactly is the job of a data analyst and get them familiarise to how does the entire data analysis process work. The session will be hosted by Shaurya Sinha a data analyst at Jio and Parag Mittal Software engineer at Microsoft.
JamesRandall / StravaRideAnalysisA sample application for React and the Strava API designed to illustrate common problems and there solutions
jordanmalecki / OnemapAggregate and visualize OneWheel ride data with Python. Filter and plot rides based on location, enhance your OneWheel experience. Enjoy life.
MinnPost / Minnpost Nice RideNice Ride data analysis
KumawatCodes / Nyc Mta Ridership Analysis PythonA data science project analyzing NYC MTA daily ridership trends post-COVID using Python.
Rob217 / TicketToRideAnalysisStatistical analysis of the USA map for the board game 'Ticket to Ride'
Pravinchavan321 / MTA Ridership Recovery Analysis Post Pandemic Trends1This project is about MTA Ridership Recovery Analysis: Post-Pandemic Trends.
patelhitakshi28 / Analysis Of Rider MetricsAnalysis of Rider Metrics: Duration, Distance, and Calories Burned
Geo-y20 / Uber Rides Data AnalysisThis project aims to analyze Uber ride data to understand various aspects of ride usage, such as the distribution of rides across different categories, purposes, months, days, and times.
Fr0sTnUb / MTA Daily Ridership AnalysisA Data analysis of Metropolitan Transport Authority Transits before, during, and after pandemic
ev-log-bot / Ev Log BotA telegram bot that captures the ride details of Ather EV and provide analysis.
sheetalbongale / Scooters In Austin Data AnalysisProject analyzing the City of Austin's Open Data for 8.4M shared scooter rides and also compare the city's 311 complaints about the same. Find insights about the popular spots for scooter rides and the correlation if these areas also have more scooter complaints and more | Python Project 1 | UT Data Analysis and Visualization Nov 2019 - May 2020
EdoWhite / ThemeParkAccidents RDF SPARQLWeb app that provides an analysis of theme park ride accidents using Semantic Web technologies (RDF & SPARQL). Made with Python.
yakubszatkowski / Cyclistic Ride Analysis ChicagoCapstone project of Google Data Analytics course
genielab / Network Analysis Ticket To RideThis repository holds all the supporting code for the blog post
AFARNOOD / Dynamic Pricing MLThis project focuses on Dynamic Pricing by leveraging machine learning to predict the cost of rides based on factors like demand, customer loyalty, ride duration, and vehicle type. Using the Dynamic Pricing Dataset from Kaggle, the project includes exploratory data analysis (EDA), feature engineering, model training, and deployment.
