Lecture 1 Counting

Yappin bout neuron networks

Where do AI networks get their intelligence from?

$\rightarrow$ well set weights: perfect weights $=$ high intel.

Do we hire grad students to go and fiddle around with those weights?

$\rightarrow$ learn with examples.

Counting

How many possible outcomes are there?

Step Rule of Counting (aka Product Rule of Counting)

If the experiment has two steps $ \to A \to B $

  • 1st step’s outcomes are from Set $ A $, where $ |A| = m $,
  • 2nd step’s outcomes are from Set $ B $, where $ |B| = n $.
  • and $ |B| $ is unaffected by output of first step.

Then the number of outcomes of the experiment is $$ \boxed{ |A| \cdot |B| = m \cdot n } $$

Example: a pixel could be one of $ 256^3 \approx 17000000 $ different colors (RGB).

There’s finite resources in the world but there’s almost infinite unique combinations of them.

Sum Rule of Counting

If the outcome of an experiment is either from set $ A $ OR set $ B $

  • where $ A \cap B = \empty $ (they are multually exclusive).

Then the total number of outcomes of the experiment is $$ \boxed{ |A| + |B| = m + n } $$