For our last class, we will look at how we can use data science to gather our models for training and testing then use those data sets to carry out those tasks. We will cover some of the principles of how to divide our data sets between the training and testing tasks as well as ways of using the training results to tweak our network design. We will end our class by looking at some of the chip-specific implementations of TensorFlow to build ANNs for our desired target processors.
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