can you have a code using all three types of machine learning in it? or is that how you create neural networks?

Answer 1

Hello, Arketa !
At you this photo shares for example on 9 sectors
in each of them there is a state for example 1 or 0 (you do not influence the state of the sectors, but only evaluate)
suppose the data from these sectors reads one neuron - after he considered the state of all sectors, he should draw a conclusion - a circle or a square
This conclusion he draws on the basis of the so-called "decisive function."
let's say the decisive function is - if the sum of all the values ​​of all sectors is greater than 5 - then this is a square if less then this is a circle (solving functions can be more complicated, but the very essence of the search for solutions is important)
and the essence is ->
you can not influence the input values ​​yourself, so to influence the result, you can multiply the input values ​​by a certain factor, and by varying the coefficient multiplied by the incoming value you adjust the result of the "decision function" to the desired result.

Answer 2

i am new to coding so i am not sure i follow you completely sorry.

Answer 3

what do you mean by three types of machine learning? as far as i know there are way more than three types

Answer 4

there are neural networks, support vector machines, decision trees, clustering, genetic algorithms, sparse dictionary learning and tons of other algorithms. and using stuff like compressed sensing you can achieve some cool stuff that might seem like machine learning to an outsider

Answer 5

reiforcment learning is a type of supervised learning by the way

Answer 6

then what types are there I've only heard of three types

Answer 7

supervised
unsupervised
and reinforsed
these are the only ones ive heard of

Answer 8

ok thank you