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Neural networks and back-propagation explained in a simple way

Any complex system can be abstracted in a simple way, or at least dissected to its basic abstract components. Complexity arises by the accumulation of several simple layers. The goal of this post, is to explain how neural networks work with the most simple abstraction. We will try to reduce the machine learning mechanism in NN to its basic abstract components. Unlike other posts…

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Interested in artificial intelligence, machine learning, neural networks, data science, blockchain, technology, astronomy. Co-founder of Datathings, Luxembourg

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