Spatiotemporal analysis finds correlations between spatial events to make decisions. Our focus will be on learning techniques to prioritize 911 calls and 311 requests to improve health and safety in our communities.

Practice these skills by participating:

  • Test causal relationships between time series
  • Forecast values of a time series with vector autoregression
  • Find buildings in satellite images with convolutional neural nets
  • Fit autoencoders to initialize a deep architecture with pylearn2
  • Train generative stochastic networks on GPUs
  • Compare optimization techniques in scipy.optimize
  • Search nearest neighbors with pykdtree
  • Minimize network connection length with networkx
  • Cluster topics with latent dirichlet via gensim
  • Select models through cross-validation
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Spatiotemporal analysis for community health and safety
Founded Sep 28, 2013

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