Fighting Illegal Dumping in Mexico Through Building a Predictive Model
Challenge Background
Environmental conservation has many different factors and in Mexico one of the most influential is the relationship with dumping sites and garbage collection. Many places in Mexico are severely affected illegally and some of them are regions of nature that must be protected.
Goal of the Project
- To identify and visualize in a map spatial patterns of existing TrashOut dumpsites.
- To predict potential dumpsites using Machine Learning and visualize them with a heatmap.
- To understand and describe patterns of existing dumpsites to prevent future potential illegal dumping(s) with an unsupervised model.
Project Timeline
What you'll learn
1. How to use Google Earth Engine for further visualization and data modeling.
2. How to visualize certain regions in a map and create filtered visualizations.
3. How to create a heat map based on ML predictions.
4. How to describe unsupervised models applied to illegal dumpings.
5. How to train and deploy image recognition models.
First Omdena Local Chapter Project?
Beginner-friendly, but also welcomes experts
Education-focused
Duration: 4 to 8 weeks
Open-source
Your Benefits
Address a significant real-world problem with your skills
Build your project portfolio
Access paid projects (as an Omdena Top Talent)
Get hired at top organizations
Requirements
Good English
Suitable for AI/ Data Science beginners but also more senior collaborators
Learning mindset
Application Form
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