NEW Python for Beginners Course Starts July 27! View Course

Made at Metis: Waste Analysis + Building Data Science Solutions

By Emily Wilson • August 01, 2018

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

__________

Take a look around and you might notice some waste. It could come in the form of something physical that you can see or feel or smell. Or it might be invisible to the eye, like wasted time or resources due to lapses in efficiency. Two recent Metis graduates took an interest in these different forms of waste and used data science to come up with ways to minimize negative impact and maximize positive solutions. 

Read about the projects here: 

Travel Time Optimization with Machine Learning & Genetic Algorithm
Vladimir Lazovskiy  
Metis Graduate

In this project, Vladimir explores how delivery companies can use the power of machine learning to forecast travel times between two locations and use the genetic algorithm to find the best travel itinerary for each delivery truck. He's interested in the wasted time generated by inefficient route planning. For example, he writes: "Consider this: a UPS driver with 25 packages has 15 trillion possible routes to choose from. And if each driver drives just one more mile each day than necessary, the company would be losing $30 million a year."

Read his blog post to understand how he used the project to tackle the large and small elements of the overarching question, "what is the relationship between machine learning and optimization?"

__________

Everyone Poops
Mattie Terzolo
Metis Graduate

In San Francisco, human waste is a growing issue, writes Mattie – both for the people who run into it and for those who have no other option than to relieve themselves on public streets. To combat this, he built a model to predict where and when human waste will show up. This sort of model could be used to better inform resource allocation for programs like San Francisco’s Pitstop (a program that brings portable bathrooms to areas that have high homeless populations).

"I believe this model adds to our current understanding by identifying the geographic and temporal underpinnings of the problem. That means when neighborhoods change, as they inevitably do, the model will be able to continue to provide accurate predictions. I hope that this can help advance efforts to keep San Francisco’s streets clean and provide citizens with the services they deserve," he writes on his blog. 

To learn more, read the post about his project here.

__________

See more examples of Metis student projects here


Similar Posts

alumni
From Analyst to Data Scientist, Grad Finds Her Way Via the Bootcamp

By Emily Wilson • July 02, 2020

This is Vickie Chan’s second time working at Fitch Ratings, one of the largest credit rating agencies in the United States. The first time exposed her to data science; now, she is a Data Scientist. Read how the bootcamp helped her make the transition.

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
Alumni Blog Spotlight: Linda Ju Shares Bootcamp Experience Start to Finish

By Emily Wilson • May 11, 2020

Bootcamp graduate Linda Ju, now a Data Science Consultant at Slalom in Seattle, recently took to Medium to write a blog series about her career transition from finance to data science and how her experience in the Data Science Bootcamp helped her get there.