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Backpropagation for softmax: Complete math explained
12:02
MSNLearn With Jay
Backpropagation for softmax: Complete math explained
Derive the Equations for the Backpropagation for Softmax and Multi-class Classification. In this video, we will see the equations for Backpropagation for Softmax and Multi-class Classification In the previous video on Backpropagation, we derived the equations for binary classification. Now its time to understand the equations for Multi-class ...
1 day ago
Backpropagation Explained
Backpropagation in neural networks step-by-step explained
21:04
Backpropagation in neural networks step-by-step explained
MSNLearn With Jay
1 day ago
Does The New Forward Only Learning Algorithm Live Up To The Hype?
18:44
Does The New Forward Only Learning Algorithm Live Up To The Hype?
YouTubeRichard Aragon
1.2K views2 days ago
#TECH: Geoffrey Hinton Says AI Has Been “Underhyped” in Recent Years Speaking at the GITEX AI Europe event, AI pioneer Geoffrey Hinton reflected on decades of AI hype cycles, recalling the optimism of the 1980s when backpropagation first gained traction and researchers overestimated how quickly progress would arrive. While acknowledging that early enthusiasm sometimes ran ahead of reality, Hinton argued that today’s situation is different. In his view, the rapid advances of the past few years me
0:24
#TECH: Geoffrey Hinton Says AI Has Been “Underhyped” in Recent Years Speaking at the GITEX AI Europe event, AI pioneer Geoffrey Hinton reflected on decades of AI hype cycles, recalling the optimism of the 1980s when backpropagation first gained traction and researchers overestimated how quickly progress would arrive. While acknowledging that early enthusiasm sometimes ran ahead of reality, Hinton argued that today’s situation is different. In his view, the rapid advances of the past few years me
TikTokentrelligence
835 views1 day ago
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TikTokentrelligence
Neural Networks adalah algoritma jaringan saraf buatan yang meniru cara kerja otak menusia tetapi dengan cara yang matematis dan statistik, yang isinya adalah neuron palsu imajiner yang sebenarnya adalah persamaan aljabar z = x1w1 a2w2 a3w3 ... axwx b, intinya saraf menerima input, lalu di kali bobot dan di tambah bias, dan jika output salah maka proses ini akan di ulang kembali lewat algoritma backpropagation (koreksi kesalahan output dengan membalikan nilai ke arah input) dan gradient descent(
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