In the last video in this series, we discussed the biologically inspired structure of deep leaning neural networks and built up an abstracted model based on that. We then went through the basics of how this model is able to form representations from input data. The focus of this video then will continue right where the last one left off, as we delve deeper into the structure and mathematics of neural nets to see how they form their pattern recognition capabilities!
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