Ch 12

All the the nodes prior to the output nodes essentially 'guess' at the correct weights. Then the algorithm checks to see if the initial guess is correct (usually not). When it is wrong...

.... it tries again (runs another epoch)

Each of the connections between nodes as a connection, each of those connections has a ________

Activation Function

Deep Neural Networks have only 1 hidden layer and multiple input layers.

False

Neural Networks in computing are exactly the same as the neural networks from biology.

False

Neural networks are an unsupervised technique, because there is no target variable.

False

The example we walked through was from a fairly famous dataset for learning about machine learning. The dataset is called:

MNIST

Hidden Layer

Something you don't see, here there is some computation to transform the X's into the Y.

An example this week was done in a Jupiter like environment called Google Collab. What was the language that was demonstrated in the videos? (One cool thing about this is that is looks just like any other package! Installing this on your own is tricky)

TensorFlow

Input Layer

These are the X's, or inputs from your data

output layer

These are the Y (the Target variable you are interested in)

(from our possibly overly simplistic explanation) In the attempt to fit values from the input layer to the output layer, the hidden layer applies some weights to the input values.

True