With the pre-made estimators provided by Tensorflow, the model training, evaluation and prediction is relatively easy the hard part is dealing with the data and dimensions.It is the epitome of senseless, mass-example-based learning, which is ironic given that the neural network architecture has its origins in biology and the human brain.įor those looking to embark on such a project themselves, a few of my more significant takeaways from this experience: It still surprises me that while a good Arena player would consider many factors when making choices like tempo, value and synergies, a deep learning model built with Tensorflow doesn’t rely on you specifying what trends it looks out for. Being an avid Arena player, I’ve always wanted to dig deeper into the inner workings of the HearthArena algorithm, and with my newly learnt skills in Tensorflow, this became a reality.
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