2. Implementation of AND function using PERCEPTRON model | Artificial Neural Networks

This video covers the step by step explanation of implementation of AND function using PERCEPTRON model. The implementation of AND function using perceptron model is useful in understanding other problems related to linear separability like OR implementation.
(Single layer perceptron model/perceptron example/ logic and gate implementation using perceptron neural networks/ logic gates implementation using neural networks)
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[@MMadni-ke9nw]

For Perceptron topic this is the best video Thanks sir

[@dr.krishankumargurukulkang1074]

Thank you very much

[@alidakhil3554]

The subject is wonderful, and !! Your hand writing on board is fabulous

[@dr.krishankumargurukulkang1074]

Thank you very much

[@singhamitgkv7709]

Verry usefull vedio for understand deep knowledge of perceptron model.

[@dr.krishankumargurukulkang1074]

Thank you very much

[@devendrasoman6404]

Thank you sir! Great explanation

[@harshvardhan8280]

Thank you so much sir for this nice video lecture in neural networks 🙏

[@parthdandawate7245]

Great Explanation keep making such videos sir thank you sir

[@technoedutech3990]

This is very helpful sir g...

[@shabanarp6116]

best explanation ever seen for perceptron..

[@dr.krishankumargurukulkang1074]

Thank you very much

[@darshanruikar4234]

best video best explanation

[@dr.krishankumargurukulkang1074]

Thank you very much

[@pareenapadwal9105]

This was very helpful... Thank you :D

[@mango-strawberry]

great explanation

[@devanshi4130]

Excellent explanation thank u

[@rajdeepsingh-ij6hi]

excellent

[@harshvardhan8280]

It helped me a lot to understand about labelled data

[@rakshitmittal5845]

very well explained...best video of perceptron

[@dr.krishankumargurukulkang1074]

Thank you very much

[@LakkojuHemanth]

nice explained thank you so much sir no words are coming to praise your efforts sir
😄😄😄😄😄

[@vinayakumarsethi9240]

Nicely explained.

[@nitishmc6929]

Very good explanation Sir 👍🙏

[@lakshmiswarupa4375]

excellent
sir

[@satyamkumar521]

best explanation sir............

[@dr.krishankumargurukulkang1074]

Thank you very much

[@jeeteshsingh5747]

Very well Explained. Helped me! Thank you sir.

[@dr.krishankumargurukulkang1074]

Glad to hear that

[@beater_y363]

True that!

[@balunqui1126]

Thank you sir..

[@dr.krishankumargurukulkang1074]

Thank you very much

[@ritikarathi9487]

Very helpful sir

[@dr.krishankumargurukulkang1074]

Thanks

[@santoshkumar4041]

Very helpful...

[@dr.krishankumargurukulkang1074]

Thank you very much

[@md.mamunurrashed9802]

Sir it helps me a lot!!

[@dr.krishankumargurukulkang1074]

Thank you very much

[@vandanathakur7511]

Good one

[@dr.krishankumargurukulkang1074]

Thank you very much

[@roshanantony]

Thank u sir!

[@mohitbhatta4046]

After watching this video I subscribed to your channel sir ! Very good explanation ❤️ keep going

[@dr.krishankumargurukulkang1074]

Thanks for kind your support..

[@shivamsharma1000]

Very well explained sir. It really helped me.. Thank you so much sir for this video.

[@dr.krishankumargurukulkang1074]

thanks

[@dr.krishankumargurukulkang1074]

Thanks for complement. Please watch my next video on implementation of backpropagation networks on or before 6-Dec-21.

[@singhpankaj7330]

thank you very much sir ...please upload more videos....

[@dr.krishankumargurukulkang1074]

Thank you very much I will soon upload more videos

[@anonymousperson7054]

nice explain . plz add more examples of it

[@moosajatt219]

easy to understand 👌

[@dr.krishankumargurukulkang1074]

Thank you very much

[@faizaomer5737]

Well explained 👌

[@dr.krishankumargurukulkang1074]

Thank you very much

[@T7GHONEY]

Nice lecture

[@examvidya2192]

Thanks sir

[@RajVerma-mc2pj]

Great sir

[@dr.krishankumargurukulkang1074]

Thank you very much

[@bhaskarkumar8146]

Thanks sir nice explain I am also student of gurukul kangri

[@dr.krishankumargurukulkang1074]

Thanks

[@coffeewithconcepts862]

Thnk you sir

[@dr.krishankumargurukulkang1074]

Thank you very much

[@whogauravmishra]

What will be the learning rate value in Matlab program of this implementation?

[@prabhakaranb6782]

Is there any learning to predict the weights exactly in the first turn itself.....by using decision separate line?????

[@aayushshrestha1655]

Nope. Then there wont be any LEARNING. these are essentially LEARNING TECHNIQUES so the network has to learn to get the ouput..
For doing that its important to follow these steps

[@akashrathod3995]

Learning rate alpha is everytime 1 or is change ?

[@DeepakKumar-ee5up]

After third input pattern the value of Yin should be 1

[@javdanjavdan9108]

عالی

[@TheIntervurt]

For Δw you use the formula atxi, shouldn't it be a(target-output)xi ?

[@chitralalawat8106]

Great😎

[@dr.krishankumargurukulkang1074]

Thank you very much

[@nikhilparihar9922]

In the second input we took bias eqauls to 0 but how
Because the previous bias was 1

[@dr.krishankumargurukulkang1074]

I will get back you soon and thanks for query.

[@madhvendrasingh806]

❤️👍

[@dr.krishankumargurukulkang1074]

Thanks

[@tusharkumar9455]

can someone please tell me how second EPOCH has been calculated .. tomorow is my exam please help...

[@vengeance1424]

Sir why and when should we take epoch 2!! Please reply

[@dr.krishankumargurukulkang1074]

To get final weights we take more epochs. Our main aim in neural networks is to get final values. Once saturation is there in values we stop.

[@vengeance1424]

Sir so the when the y values and target values become equal then we stop doing further procedure. Right sir??

[@metasebiyabizuneh368]

Sir, thanks to the brief explanation. But I don't understand what the ephoch 2 is. How do we find everything on epoch 2?

[@dr.krishankumargurukulkang1074]

Values of Epoch 2 has been written directly but can be calculated like epoch 1 which I have explained in this video.

[@ShashankDiwakar-vw4dq]

​@@dr.krishankumargurukulkang1074 are sir lekin kaise calculation krenge yahi to pucha

[@ananya_sinha050]

Where is for or function??

[@ravisankar2086]

Hi sir, your explanation is superb sir. I need one help for the neural networks please suggest me text book

[@dr.krishankumargurukulkang1074]

Zacek M Zurada

[@aayushshrestha1655]

Sir please can you do using this method for OR gate too.
You've explained brilliantly..
For OR logic im getting final weights and bias as. w1=1. w2=1 b=1

[@dr.krishankumargurukulkang1074]

Please apply the same for OR gate too. The method is almost same. You just try it, if face any problem kindly let me know.

[@aayushshrestha1655]

@@dr.krishankumargurukulkang1074 okay sir. Thank you ♡

[@vinitraj6268]

Can we start by taking x1 = -1 , x2 = -1 and target= -1

[@dr.krishankumargurukulkang1074]

Yes; but in all epochs same sequences to be followed

[@mishraw]

i love u

[@lullubi5957]

Don't erase the board with hand please 🙏. I think It's not healthy 🙂

[@yarlagaddapurna1631]

Sir,can u make videos on THESE sir ,i have exam in this week KLUNIVERSITY STUDENT SIR
ARTIFICIAL INTELLIGENCE IS MY SUBJECT SIR ,
1.demonstrate how an XOR function CAN BE REALIZED USING AND gate and an OR GATE
,SUBSEQUENTLY DESIGN A SUITABLE MULTILAYER PERCEPTRON WHICH CAN implement this XOR function
2.design a suitable perceptron which can be used to realize a 4 input logical AND gate
3.design a suitable perceptron which can be used to realize a 4 input logical OR gate
4.

[@dr.krishankumargurukulkang1074]

okay

[@yarlagaddapurna1631]

@@dr.krishankumargurukulkang1074 give me ur number sir

[@yarlagaddapurna1631]

@@dr.krishankumargurukulkang1074 i have exam in 1 week of january sir

[@sumedhravi7598]

Please use a mic.....Cant hear you clearly