Artificial Neural Networks – Plan of Attack
(For the PPT of this lecture Click Here)
To help you overcome the complexities inherent in Neural Networking, SuperDataScience has developed a seven-stage Plan of Attack, which is hopefully not a precursor to what our creations do when sentience awakens within them.
The Neuron
Building from up from the foundation of the Neural Network we will first examine the Neuron; how it works and what it looks like. It is the centerpiece of the Neural Network. For point of comparison, there will be some examination of the human brain; how that works and why we want to replicate it.
The Activation Function
The next stage will cover The Activation Function. This is the process applied to data within the neuron. We will be exploring which are most commonly used and understanding which is most appropriate for your Neural Network.
Practical Application
Then we get into some deep learning on the machinations of the Neural Network. We will follow one in action to see what we are striving towards. But instead of the T2 slicing open his flesh to reveal the robot skeleton beneath, we’ll be looking at how a Neural Network can predict housing prices. Not as dramatic but potentially just as upsetting.
How Neural Networks Learn
The next three tutorials will focus on what makes Neural Networks so fascinating; how they learn. We will be going into deep learning with the Gradient Descent method. Then we will move on to its refined sibling, the Stochastic Gradient Descent method.
If by this point fiery flashes of Judgement Day have not interrupted your thinking completely, we will have a summary section that covers Backpropagation and how to compile a set of instructions for your Neural Network.
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