backpropagation
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Using PyTorch Torch vision for pretrained AlexNet models
In this tutorial, we will discuss PyTorch and Torchvision’s pretrained models, focusing on AlexNet. AlexNet is a convolutional neural network…
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An Introductory Guide to PyTorch Gradients: Understanding the Basics for Beginners
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Understanding Loss, Backpropagation, and Gradient Descent: A Beginner’s Tutorial on DQN using PyTorch
DQN PyTorch Beginners Tutorial #6 – Explain Loss, Backpropagation, Gradient Descent DQN PyTorch Beginners Tutorial #6 – Explain Loss, Backpropagation,…
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Building ResNet PyTorch model with residual connections for deeper networks
ResNet PyTorch model from scratch ResNet PyTorch model from scratch: residual connection enables deeper network ResNet (short for Residual Network)…
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NeRF: Neural Radiance Fields implementation in PyTorch with 100 lines of code | NeRF#5 “`python import torch import torch.nn as nn import torch.nn.functional as F class NeRF(nn.Module): def __init__(self): super(NeRF, self).__init__() # Define neural network layers here def forward(self, input): # Implement forward pass logic here return output model = NeRF() optimizer = torch.optim.Adam(model.parameters(), lr=0.001) # Training loop for epoch in range(num_epochs): for i, data in enumerate(train_loader): inputs, targets = data optimizer.zero_grad() outputs = model(inputs) loss = F.mse_loss(outputs, targets) loss.backward() optimizer.step() if i % 10 == 0: print(f”Epoch {epoch}, Iteration {i}, Loss: {loss.item()}”) “` This code snippet outlines the basic structure of a Neural Radiance Fields (NeRF) implementation in PyTorch. The `NeRF` class represents the neural network model, with customizable layers and a forward pass method. The code also includes an optimizer setup using Adam and a training loop that iterates through batches of training data, calculates the loss, performs backpropagation, and updates the model parameters. The model can be further customized with additional layers, activation functions, and training parameters to fit specific use cases.
NeRF in PyTorch NeRF – Neural Radiance Fields in PyTorch NeRF, short for Neural Radiance Fields, is a deep learning…
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Building a GPT Model from Scratch Using PyTorch and Python: A Neural Network Transformer Deep Learning Project #chatgpt
Create GPT From Scratch – Neural Network Transformer Deep Learning Creating GPT From Scratch Generative Pre-trained Transformer (GPT) is a…
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