Building your first Neural Network

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This is the first in a playlist of videos where are are going to talk about the fundamentals of building neural networks!
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[1] Code to build first neural network: github.com/ajhalthor/deep-lea...
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Пікірлер: 23

@CodeEmporium 5 ай бұрын

What other playlists should I make? Also, If you think I deserve it, please consider giving this video a like. Subscribe for more content like this.

@mehedihassan7824 5 ай бұрын

can you make some videos on implementing the transformer models in code?

@aligharaeini5971 2 ай бұрын

one of the best videos ever about NN , congrats

@apollokre1d 5 ай бұрын

Love the videos, liked and subscribed, looking forward to the series.

@CodeEmporium 5 ай бұрын

Thanks so much! Definitely more to come every week

@joachimguth6226 5 ай бұрын

Impressive the clarity of layout and speech.

@CodeEmporium 5 ай бұрын

Thanks for the kind words.

@prashlovessamosa 3 ай бұрын

your 101 series are super informative.

@rashedulhasanrijul5506 3 ай бұрын

Thanks for such a nice explanation

@katariya608 3 ай бұрын

its the algorithm to recommend me your video

@user-bp2ol4wi1c 5 ай бұрын

Would be cool if you ran though process of building a Neuron class step by step, to better understand how all parts integrate in code as we go before using more advanced libraries. So more step by step bottom up element by element building. I think it would be good way to practice learners intuition about all this. I found many of your videos highly educational. Great content!

@mindurownbussines 5 ай бұрын

Probably some recommendation system in youtube algorithm. That's what we use everday, even the poor

@CodeEmporium 5 ай бұрын

Yep that’s a good example of AI that isn’t very apparently AI to most

@testuser2709 5 ай бұрын

I think I use a PID type AI most

@pradnyakarve6094 3 ай бұрын

Hello, could you please let me know why the following error ? RuntimeError: mat1 and mat2 shapes cannot be multiplied (1x5 and 4x6) code: with torch.no_grad(): model.eval() correct = 0 total = 0 for batch_x, batch_y in test_loader: outputs = model(batch_x) predicted = torch.max(outputs, 1) total += batch_y.size(0) correct += (predicted == batch_y).sum().item() accuracy = correct / total print(f'Test accuracy:{accuracy:.2f}') class NeuralNetwork(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNetwork, self).__init__() self.fc1 = nn.Linear(input_size, hidden_size) self.relu = nn.ReLU() self.fc2 = nn.Linear(hidden_size, num_classes) def forward(self, x): out = self.fc1(x) out = self.relu(out) out = self.fc2(out) return out