Neural Network Explained | Hindi скачать в хорошем качестве

Neural Network Explained | Hindi

0:00 Discuss about neural network. 0:02 So fundamental of neural network network. 0:06 So artificial so long time big neural network art existing network, machine learning, deep learning, artificial even 60 decade or biological neurons or artificial neuron D cell bodies action. 1:06 This term in general case, that is the flow how human brain will work the human brain or connected. 1:29 So network man competition competition finally is a mathematical format in signal and 1 to 3 function function basic artificial description in 60s evolution, 6 70s Microsoft and Apple mathematically later a computation available basic logistic linear function or this is the one function, this is final activation function but function is equal to WTX plus B is WTX plus by equal to WX plus B over. 4:13 In I think 8/9 class may 11/12 class may form linear function equal to MX plus C, right, linear function X plus C or or finally linear equation to linear equation, similar WTX plus B equation randomly defined or terminology. 5:10 This is a learning parameter. 5:16 So finally model even a basic model do something in in expected to finally, we are learning the way to complete cycle cycle, right? 6:57 Fun activation function or X plus B activation function, activation, activation function B activation function or input linear equation or B randomly or finally activation function within it activation function finally out activated output. 7:52 This is the final output you say. 8:04 So in 1211, X two code W-2 X three, W three is equal to X one double one plus BZ two equal to X two multiplied by W-2 plus BZ three equal to X three plus. 8:47 Both are in linear functionality, right. 8:50 Linear function function, a single neuron activation, right? 9:07 Single, single right two 123. 10:41 Number one, number two, right to layer number one layer number two, fully connected any activation input next layer, right? 10:52 They say first activation in second input is right. 11:07 So finally, right. 11:33 So or finally, this is the output layer output may output I be happy with the multiple activations but output upon the single tree easily. 11:43 You have a neuron number of activation is one input is three hidden activation for output may 1 activation, right computation formula plus form semi formula, right W three X plus B finally +123441 X two X three, X two, X 32 X plus W one X two plus W-2 X two plus plus XB or or artificial artificial neural network, basic artificial artificial complex task or convolutional mathematical term convolutional. 14:17 I think mathematician to mathematics convolutional computation has a, to actually previous or in,, could you be sentence, sentence me? 14:54 I'm going to school. 14:56 Yeah. 14:58 Going to a school subject, going to any, any A N CNN or mostly, but mostly mostly focus or next so related without.