Extended to May 31: Summer Bootcamp Final Application Deadline Apply Now

Made at Metis: Data Science on the Move – Improving Cycling Safety and Forecasting Rideshare Use

By Emily Wilson • April 25, 2018

              Recent Metis graduate Rebekah Cunningham riding with a group near Mt Zion, Utah

This post features two final projects created by recent graduates of our data science bootcamp.
Take a look at what's possible in just 12 weeks.

_____

In this month's edition of the Made at Metis blog series, we're highlighting two recent student projects that focus on the intersection between transportation and data science. One project is a video-based car detector to improve safety for city cyclists, and the other presents a way to better forecast hourly Uber demand across New York City neighborhoods. Read more about both below:

Car Back! A Video-Based Car Detector for Cyclists
Rebekah Cunningham
Metis Graduate

Rebekah Cunningham loves to hit the open road on her bicycle, enjoying the fresh air while exercising and taking in the views. But the hobby can be a dangerous one, especially when navigating city roads, where cars generally rule the roost. To address the dangers associated with city cycling, Rebekah created Car Back!, a video-based car detector for cyclists as her final project at Metis. 

In a recent blog post about the project, she explained that the phrase "Car Back!" is what one cyclist shouts to another to alert them of an approaching car from behind. In the post, she detailed the project's ambitious goal: "My vision is to be able to attach a camera to the back of my bike, near the seat which captures video in real time and alerts of any cars that are approaching from behind. The alert would be an audio cue that is played in one of the apps that is already running -- Strava, Spotify, or Audible as examples. " 

To get started...she went cycling, of course! "I strapped a GoPro to the back of my bike and set out for a number of routes to collect video data to train a model.  I needed to be thorough in capturing a variety of weather conditions, lighting conditions, and traffic conditions.  From these videos, I extracted frames at 6 frames per second using ffmpeg and set about hand-labeling these frames for approaching cars.  I drew rectangles around approaching and not-approaching cars and labeled them appropriately using a tool called RectLabel," she wrote.

Read the full post here to learn how she got from that first step to the end result – a model with 97% recall. (And see a demo video, too!)

_____

Forecasting Uber Demand in NYC
Ankur Vishwakarma
Metis Graduate

Ankur Vishwakarma wanted to blend three things he likes into his final bootcamp project: urban transportation, geographic visualizations, and time series forecasting. To make it all work together, he decided to focus on forecasting hourly Uber demand across New York City neighborhoods. This type of improved forecasting could help customers and companies alike in a number of ways, including alerting drivers of upcoming demand, improving customer satisfaction, and aiding traffic planning. 

"In addition to time-lagged features (such as previous week’s demand), I added information specific to each neighborhood to improve my predictions," he wrote in a blog post about the project. "As a final result, I obtained relatively accurate unique forecasts for all neighborhoods in NYC."

How'd he do it? Read the full post for a detailed breakdown of each step (see his project pipeline pictured below), including what went right, what went wrong, and how it all turned out. 

_____

Curious what else Metis graduates have created as final projects? See more examples here


Similar Posts

alumni
Infographic: Metis Bootcamp Alumni By The Numbers

By Metis • March 26, 2020

In this infographic, we break down a data set that’s near and dear to our hearts: one that represents our Data Science Bootcamp alumni. Find out where our grads are working and within what industries, where many of them call home across the United States and the world, what they studied pre-bootcamp, and much more.

alumni
Made at Metis: Street Art to Fine Art; Building a Recommendation System

By Metis • May 26, 2020

This post features two projects from recent graduates of our data science bootcamp. Take a look at what's possible to create in just 12 weeks, including a project to leverage a user’s existing street art preferences to recommend visually-similar fine art and a project to develop a collaborative filtering recommendation system using sales transaction data.

alumni
The Trifecta: From Bootcamp Prep Course to Bootcamp to New Career

By Emily Wilson • March 05, 2020

For Kari Davis, there’s before the bootcamp, and there’s after. A clear demarcation between two paces of professional life – one slower and more bureaucratic, the other fast-paced and constantly changing. Learn how a Metis Bootcamp Prep Course helped her prepare for the bootcamp and then land a new data science job.