so… let’s play a game !!!

i’ll show you a series of patterns, and each pattern maps to a value of either 0 or 1

now consider this pattern, which number would this pattern map to?

if you said 0 you’re probabily right

if you said 1 you’re also probabily right

¯\_(ツ)_/¯

the point here is that whatever your guess was…

- you had no idea what each of the tiles represented
- you had no idea what the co-relation between the tiles was
- you had no idea what 0 or 1 represents

just like AI and this guy here

he has 0 understanding of what the puzzle means and what his guess means, but he made the correct guess

## The Learning Problem

the game we just played right now, is presicely what every **ML/DL/RL/AI** algorithm does

- take data that has been cleaned/processed (into a puzzle)
- find a pattern in the data
- use the pattern on new data (it has never seen before)
- hope it gets appriciated

but keep in mind that not every problem can be solved this way

because…

- not every problem has (enough) data on it
- not every data has a pattern in it

some of them also/already have a (not so) simple mathematical answer to them, you don’t need rely to finding patterns

but for the rest, they can probabily (maybe not efficiently) be solved by having **a computer find a pattern** AKA **learning from data**

## How does a Computer Learn from Data

short answer, you solve the learning problem 😝

long answer to solve any **learning problem** (ML, DL, RL)👇

**unknown solution:**think of this the true pattern/source of all the data we have**training data:**data that we have collected and processed so a computer can find a pattern**learning algorithm:**the actual algorithm that refines a model so the model learns from the dataeg: Perceptron Learning Algorithm, Backpropagation Algorithm, etc

**hypothesis set:**a set of all possible models that can find a solutioneg: Perceptron, Neural Networks, etc

**final hypothesis solution:**a pattern with the heighest accuracy

while this **IS** the long answer to solve any **learning problem**

this long answer lacks details… the details which would be dealt with in the forthcoming blog articles

untill next time !️ ✌

or you could spot me in the wild 🤭 i mean instagram, twitter, linkedin and maybe even youtube where i excalidraw those diagrams