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AI — PyTorch

What is PyTorch?

Open-source deep learning framework by Facebook.

Install

pip install torch torchvision

Basic Model

import torch
import torch.nn as nn
import torch.optim as optim

class SimpleNet(nn.Module):
    def __init__(self):
        super().__init__()
        self.fc1 = nn.Linear(784, 128)
        self.fc2 = nn.Linear(128, 10)
    
    def forward(self, x):
        x = torch.relu(self.fc1(x))
        x = self.fc2(x)
        return x

model = SimpleNet()
criterion = nn.CrossEntropyLoss()
optimizer = optim.Adam(model.parameters())

Training Loop

for epoch in range(10):
    for batch in dataloader:
        optimizer.zero_grad()
        output = model(batch.data)
        loss = criterion(output, batch.target)
        loss.backward()
        optimizer.step()

Mini Practice

  1. Install PyTorch
  2. Build neural network
  3. Train model
  4. Compare with TensorFlow

Up Next

Continue with OpenAI — OpenAI API.

Related Topics

Frequently Asked Questions about PyTorch

What is PyTorch in AI?

PyTorch is a fundamental concept in AI. This lesson explains it step by step with clear examples, making it easy for beginners to understand.

How do I learn PyTorch?

Start by reading the explanation above, then try the code examples. Practice by modifying the examples and experimenting with different values. Hands-on practice is the best way to learn PyTorch.

Why is PyTorch important in AI?

PyTorch is essential for AI development. Understanding this concept will help you write better code and solve real-world problems more effectively.