machine-learning - Smartest neural network architecture

Question

I am very new to neural networks and only a lowly programmer. I don't have a firm grasp of the different neural network architectures. My question is this: what is the smartest architecture? Which network is the fastest learning, can recognize the most complex and vague patterns and is the most adaptable. I've been reading about all sorts of cool networks like the echo state and liquid state machines and long short-term memory networks but I really have no clue about how these work or which to use in what context. If you know how these crazy networks work I'd like to hear your thoughts.

thanks!

Answer 1

没有你要寻求的东西。有很多不同类型的网络，因为有很多不同类型的问题，没有人知道做某事的“最佳”方式是。它是一个正在迅速发展的活跃研究领域。某些类型的网络在某些任务中变得越来越普遍（即：用于图像分类的卷积网络），但即使是最好的也不是一成不变的。即使是这样，也不会告诉您需要多少层或层的宽度，这甚至不会涉及到训练中网络的初始化或更新。

如果你想真正了解和了解更多关于神经网络的知识，你将不得不进行大量的自学——这需要工作和耐心。堆栈溢出之类的简单问答格式不会帮助您了解有关神经网络的大部分内容。