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Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK

Detecting small-scale mines in Ghana

Elena Terenzi (Microsoft), Michael Lanzetta (Microsoft)
14:5515:35 Thursday, 24 May 2018
Data science and machine learning
Location: Capital Suite 10/11 Level: Intermediate
Average rating: ****.
(4.00, 3 ratings)

Who is this presentation for?

  • Data scientists

Prerequisite knowledge

  • A working knowledge of convolutional neural networks and Keras

What you'll learn

  • Explore a collaboration between Microsoft and the Royal Holloway University, London, that applies deep learning to locate illegal small-scale mines in Ghana using satellite imagery and investigates their impact on surrounding populations and environment

Description

Illegal small-scale mining is a growing industry in many developing countries. In these mines, gold and other precious minerals are extracted in a low-tech, labor-intensive process. While these mines provide huge employment and income potential for poverty-stricken communities, they are also linked to environmental damages, health hazards, and social ills. However, since these small mining operations are mostly illegal, there is virtually no data to analyze their exact impact.

Michael Lanzetta and Elena Terenzi offer an overview of a collaboration between Microsoft and the Royal Holloway University, London, that applies deep learning to locate illegal small-scale mines in Ghana using satellite imagery and investigates their impact on surrounding populations and environment. The goal of the project is to enable better-informed policy decisions by relevant stakeholders. First, the team built an image classification model in Keras and scaled the training of the model using Kubernetes on Azure. Once the mines were identified, the team investigated the impact of those mines on surrounding environments and populations in Python.

Photo of Elena Terenzi

Elena Terenzi

Microsoft

Elena Terenzi is a software development engineer at Microsoft, where she brings business intelligence solutions to Microsoft Enterprise customers and advocates for business analytics and big data solutions for the manufacturing sector in Western Europe, such as helping big automotive customers implement telemetry analytics solutions with IoT flavor in their enterprises. She started her career with data as a database administrator and data analyst for an investment bank in Italy. Elena holds a master’s degree in AI and NLP from the University of Illinois at Chicago.

Photo of Michael Lanzetta

Michael Lanzetta

Microsoft

Michael Lanzetta is a principal SDE at Microsoft. In his more than 20-year career in the software industry, he’s worked in domains as varied as circuit design and drug discovery and in languages from JavaScript to F#, but his primary focus has always been scaled-out server-side work. Michael has a background in demand forecasting from Manugistics and Amazon and machine learning from Bing; he has spent the last few years building intelligent services on Azure using everything from Spark to TensorFlow and CNTK.