Spatial Data Science: Algorithms and Applications by Rappi

 

Recently, many companies are facing similar problems regarding movement of people or goods such as transportation (Uber, Lyft), food delivery (UberEATS, Rappi), grocery delivery (Instacart, Rappi, Cornershop) and so on. Due to similar companies solving alike problems, the winner could be the one with best possible algorithms for the most complex problems.

During this workshop, you will take away exposure to the most common spatial problems, how to deal with them, the tools and the trade-offs between different approaches. Some problems are spatial indexing, spatial clustering and some more. Additionally, proposed approaches will have a theoretical intuition and the practical implementation in python. The combination of data science and spatial problems haven’t had enough attention and is getting more important every year.   

Feb 24

Course Dates

Guadalajara, MX

Location

3 hrs

Course Length

30 students

Onsite limited

English

Language

Lecturers

Adrian Gomez

Adrian Gomez

Data Science at Rappi

Adrian Gomez is a Data Scientist at Rappi, he has a bachelor in computer science and a specialization in Machine Learning from the University of Washington. He’s very interested to work in the creation of supervised models, put models in production, create data pipelines, etc. He has experience in several problems related to logistic optimization such as carpooling apps, taxi apps, and delivery services apps. Currently, he’s working at Rappi in courier dispatch optimization, store coverage, and fraud detection.

Schedule

9:30-10:00 AM

Registration & Breakfast

10:00-12:30 PM

Workshop

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