Summary

In this chapter, we gained a functional overview of biological neural networks, with a small and brief preview covering concepts such as neural learning and distributed representations. We also refreshed our memory on some classic data science dilemmas that are equally relevant for neural networks as they are for other ML techniques. In the following chapter, we will finally dive into the much-anticipated learning mechanism loosely inspired by our biological neural networks, as we explore the basic architecture of an ANN. We amicably describe ANNs in such a manner because, despite aiming to work as effectively as their biological counterparts, they are not quite there yet. In the next chapter, you will go over the main implementation considerations involved in designing ANNs and progressively discover the complexity that such an endeavour entails.

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