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GTC ON-DEMAND

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Abstract:
Learn how to reconstruct missing data in specific city areas when only one source of data is available, and find out how to predict activity patterns based on historical urban data. We'll explain how we achieve this by training a neural network to learn the relationship between different types of data such as spend data and activity data. We used this approach to predict the local economic impact of building a new community center or holding a large event. We'll discuss how we use the power of modern NVIDIA GPUs to run simulations of whole cities and how we use Chronotope visualization software to let analysts explore predictions and compare these with existing situations.
Learn how to reconstruct missing data in specific city areas when only one source of data is available, and find out how to predict activity patterns based on historical urban data. We'll explain how we achieve this by training a neural network to learn the relationship between different types of data such as spend data and activity data. We used this approach to predict the local economic impact of building a new community center or holding a large event. We'll discuss how we use the power of modern NVIDIA GPUs to run simulations of whole cities and how we use Chronotope visualization software to let analysts explore predictions and compare these with existing situations.  Back
 
Topics:
Advanced AI Learning Techniques, Deep Learning & AI Frameworks
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9660
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