In my first post on neural networks, I discussed a model representation for neural networks and how we can feed in inputs and calculate an output. We calculated this output, layer by layer, by combining the inputs from the previous layer with weights for each neuron-neuron connection. I mentioned that| Jeremy Jordan
In my introductory post [https://www.jeremyjordan.me/neural-networks-representation/] on neural networks, I introduced the concept of a neural network that looked something like this. As it turns out, there are many different neural network architectures [http://www.asimovinstitute.org/neural-network-zoo/], each with its own set of benefits. The architecture| Jeremy Jordan
Teaching page of Shervine Amidi, Graduate Student at Stanford University.| stanford.edu
