### Gradient Descent Introduction

Posted:

**Sun Dec 09, 2018 2:32 pm**Hello everybody,

i am interested in a simple gradient descent implementation. Unfortunately i am not able to put the puzzle pieces together.

Here is what i think that i understand and what i can do for now:

base model:

1. i have a sample set of positions including results

2. i have a parameter list with N elements.

3. i have a cost function (MSE)

a. to minimize the cost function, which is a squared function, i need the derivative which leads to a linear model y=mx+b.

b. solved this, i can tune the parameter the way, that y=mx+b gets close to 0.

example:

1. SAMPLESIZE 10000

2. PARAMETERLIST 5

3. MSE = (sum(result-computed_value)^2) / SAMPLESIZE

How do i have to iterate over my parameterlist and the samples to compute m,b ?

Do i have to compute m,b for each single sample ? m,b for the batch ? how do i get m,b for the batch ?

I red some articles on the web, but i am interested in the dialogue and the practice how to handle it in the context chess parameter tuning.

So, i think i got the idea but need to know how to do it.

Thanks a lot in advance...

i am interested in a simple gradient descent implementation. Unfortunately i am not able to put the puzzle pieces together.

Here is what i think that i understand and what i can do for now:

base model:

1. i have a sample set of positions including results

2. i have a parameter list with N elements.

3. i have a cost function (MSE)

a. to minimize the cost function, which is a squared function, i need the derivative which leads to a linear model y=mx+b.

b. solved this, i can tune the parameter the way, that y=mx+b gets close to 0.

example:

1. SAMPLESIZE 10000

2. PARAMETERLIST 5

3. MSE = (sum(result-computed_value)^2) / SAMPLESIZE

How do i have to iterate over my parameterlist and the samples to compute m,b ?

Do i have to compute m,b for each single sample ? m,b for the batch ? how do i get m,b for the batch ?

I red some articles on the web, but i am interested in the dialogue and the practice how to handle it in the context chess parameter tuning.

So, i think i got the idea but need to know how to do it.

Thanks a lot in advance...