Build Neural Networks From Scratch

git clone https://github.com/yourusername/micrograd-plus.git
cd micrograd-plus
pip install numpy

from micrograd import Tensor
from micrograd.nn import Linear, Sequential, ReLU
from micrograd.optim import Adam
from micrograd.nn.losses import MSELoss

# Create a simple neural network
model = Sequential(
    Linear(2, 16),
    ReLU(),
    Linear(16, 1)
)

# Setup training
optimizer = Adam(model.parameters(), lr=0.01)
criterion = MSELoss()

# Training loop
for epoch in range(100):
    # Forward pass
    predictions = model(X)
    loss = criterion(predictions, y)

    # Backward pass
    optimizer.zero_grad()
    loss.backward()
    optimizer.step()

    print(f"Epoch {epoch}, Loss: {loss.item():.4f}")