Zn = factor * math.sqrt(Variance / frame_size)
High_bound = history_data[frame_size-1]+Zn
Low_bound = history_data[frame_size-1]-Zn
return [High_bound,Low_bound]
As z-score=(data we want-mean)/std deviation, so i want to understand above code by this formula. Also i want to know what history_data,mul factor and frame size signifies here in the function?
And bound[0] is value returned by high bound and bound[1] is returned by low bound?
ok i am reading this thanks for your concern
Do let me know after you read it
@vishalvats2000ys i read it and understood it as well. It is all clear now.Thank u soo much for the solution.
can i have your linked in id?
Actaully I am not very much active on social media. I haven’t updated my Linkedin profile.
In place of that, I have made a digital portfolio of mine where there is a Conatct Me section. You can drop your message there.
Link is this: https://youthful-engelbart-492f13.netlify.app/
After going through the portfolio do tell me how was it ?
Wow its great very good and well designed and managed…Nice way to utilise your skill
Thanks Still working on it
Did you go through all 4 pages i.e. work about and so on?
yes yes i saw all the parts