title: Keras neural network with a set of data repeated over time
body: <p>For a project, I'm trying to do binary classification (so 1 output of either 0 or 1) on gameplay data. My data is broken up in to 2 second sample frames, with data recorded 20 times per second. This means i have a 40 copies of my data per 2 second sample frame.
  The categories i am collecting are:</p>
  <ul>
  <li>x, y, z (spatial dimensions within the context sample frame, so the most top top left point would be 1, 1, 1 and the most bottom bottom right point would be -1, -1, -1)</li>
  <li>yaw and pitch</li>
  <li>attack yaw and pitch (same sort of data as above, but will not always be the same value)</li>
  <li>hurt time (single time value)</li>
  <li>attack time (single time value)</li>
  <li>velocity x, y, z</li>
  </ul>
  <p>This comes to 480 values total. My question is, what would be the best network layout for something like this? I'd assume some form of CNN but given the nature of the data I'm not really sure how to design it in terms of layers. As per title, I am using Keras.</p>
  <p>Could anyone point me in the right direction?</p>