Implementation of AND function using Perceptron Model 

​@@rohitchitte9155 he is defining the new activation function; he is not using the sigmoid function that we have seen in the other tutorials.

Chapri explanation

​@@wfkpk Why not use sigmoid? Any reason for that?

right it should be true - predicted

why?

Yes, you're correct. It's just a small mistake he made though and everything else should still be valid.

@@RazaHussain96 Because it's an AND function which means x1=1 AND x2=1 should give t=1 and not t=-1.

do you mean ordering of nodes within input layer?

Back Propagation algorithms are obviously useful but in this example it works without using this, but definitely for complex datasets we will require back propagation.

What is formula of Linear activation function? For using here.....

thanks✨

Same question!!

Yes correct.

welcome🤗

Thank you😃

Try it that way if you are getting final values satisying the AND condition then it will be correct👍🏻

You might have made some mistake in calculations. Because it is correct.

Thank you sir😄

Keep Learning👨🏻‍🏫

Because this video is part of the Machine Learning course and you skipped this tutorial of the course: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-ysQun8VbUmM.html

Share my videos to help my channel grow😊💯

output of y will be passed to activation function for classification

Yep that's what i said.. After passing it to activation fn the result should be either 0 or 1 according to the activation fn which u have taken.. But u are getting - 1 for some input.. Which can't be possible... If your activation fn would have classified the output to either 1 or - 1 then it was ok.. But for this act. fn that is not the case..

it is correct i have rechecked the solution in the book...

@@ThinkXAcademy I think me and Shahid have the same question, your solution might be correct but the question here is "how" did you get to the solution, "how" did you end up with a -1, *how*? thanks for the video btw.

Activation Function for this video is defined as: if input > 0 : then output is 1 if input = 0: then output is 0 if input < 0: then output is -1

Thanks😄 Share it with other students to help others too💫

Compute the same way as we did in iteration 1 but take values of bias from first iteration

yes

yes formula is needed to update the weights and bias.

@@ThinkXAcademy but in some videos and site i have seen that they have solved with using formula [ w;(new) = zv;(old) + ct.t:x; ]

@@ThinkXAcademy is using this formula [w;(new) = zv;(old) + ct.t:x; ]is compulsory or not?

it is important to use this formula because weight needs to be readjusted after each Iteration

using the formula y = w.x + b

@@ThinkXAcademy perfect, thanks!

Bro its change in wheight which we do get targeted output and reduce error during traning.

playback speed 1.5x pr krke dekhle

Wahi kiya bhai, par bata raha future k liye

haan meri new videos mei maine fast krdi h speed

btw thanks for feedback

@@ThinkXAcademy bro ek update formula mene ye bhi dekha tha: w new = w old + alpha * t * xi. Where t is either 1 or -1. Use 2 when the class should be above the line and use -1 when class should be below the line. Please reply bro if you see this, i have exam today