Limitation of Single Layer Neural Network

[@FitWithShayan]

Thank you very much, Sir. You teach such excellent that people want to learn more about ANN.

[@merlissoto3923]

Thank you Dr. Faruqui!

[@pasqualeabbate2906]

thaks a lot , you're really helping me a lot during my thesis path

[@jithmarathnayaka2298]

Very useful sessions. Thank you so much for doing these. please continue further.

[@ib257]

i cant find the next video ( 2 layers nn) it out already ? can you send me the link !! you are the best teacher I ever meet thanks for that !!!!

[@NuruzzamanFaruquis]

Thank you for your inspiring compliment. The multilayer neural network lecture is not ready yet. Please subscribe the channel and activate the bell icon. Then you will get a notification when the video will be uploaded.

[@jesusdanielolivaresfiguero4752]

Excellent, thank you very much for your help. Could you recommend a book that helps to deepen these issues?

[@eda-un8zr]

Great

[@roberteklund7208]

Isn’t both examples , a linear line y = k*x +m , Where k = the slope and m=intercept?. So how should i better understand the limitation criteria for the single neuron NN ?

[@eengpriyasingh706]

Gm sir, I am trying an input matrix in which my data is not static. I am feeding one feature of a signal of samples 1000 and another feature for 1000 samples and total element is 26 with 2 features each with 1000 samples. How to feed them

[@eylulmood4830]

Great could you please tell me which mic 'brand' you use to record your lessons I like your clear voice

[@NuruzzamanFaruquis]

I am using Boya M1 microphone.

[@eylulmood4830]

@@NuruzzamanFaruquis thank you a lot :)

[@ravijaiswal2536]

Hello sir, i have one question can we train cnn model with have a fingerprint bits string matrix vector to predictive model.

[@shirishaboddupally9000]

Thank you sir

[@NuruzzamanFaruquis]

All the best

[@shirishaboddupally9000]

Sir can u give example for 7 inputs with 2 outputs neural network

[@NuruzzamanFaruquis]

I will cover classification at output layer in upcoming lessons.

[@mukeshverma-ut8kg]

thanks.

[@NuruzzamanFaruquis]

You are most welcome