#3. Backpropagation Solved Example Train Neural network predict output Updates Weights by Dr. Mahesh

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#3. Backpropagation Solved Example Train Neural network predict output Updates Weights by Dr. Mahesh Huddar

The following concepts are discussed:
______________________________
How to Build a neural network?
How to assign weights to the neural network?
How to train the Neural Network?
How to predict the output with respect to the given input?
How to find the error?
How to update the weights so that we can reduce the error?
Gradient Descent rule to update the weights.

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This was very clear and useful, thank you

jahanvi

Pls make a vedio on 1.Multivalued logic in fuzzy arithmetic

2.Linguistic hedges and Lingusitic variables. With examples

3.explain classical logic and classical set..

4 fuzziness of fuzzy set and crisp set with Numeircals.

Thank you ❤

souravbhagat

pls upload video on GRU fundamentals with solved examples like this video and GRU multivariate time series prediction using matlab..This video is very helpful

sukritipatty

I have a doubt for weight adustments in the previous videos you have used a different formulae but here you have used a different forumales which one is correct ?

adithyar

Pls upload videos on computational learning theory and evaluation hypothesis from tom Michel

ramalakshmi

so, what u taught earlier about calculating y = f(a) and error = ( t-o )..All that was wrong ?

AdityaSingh-qlke

Why did you not use sigmoid function sir

prajwalm.s

can you explain wit Sigmoid activation function? i need it badly.

AliRaza-uzsw

Please upload videos for k meloids (PAM) algorithm sir🙏🙏

anjanavenkat

Pls upload random forest algorithm numerical example

varunthejaredapaka

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