deep-learning
Build and train neural networks with PyTorch - MLPs, CNNs, and training best practices
npx skills add majiayu000/claude-skill-registry --skill deep-learning --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Deep Learning Skill > Build and train neural networks using PyTorch. ## Quick Start ```python import torch import torch.nn as nn from torch.utils.data import DataLoader, TensorDataset # Define model class SimpleNN(nn.Module): def __init__(self, input_dim, hidden_dim, output_dim): super().__init__() self.layers = nn.Sequential( nn.Linear(input_dim, hidden_dim), nn.ReLU(), nn.Dropout(0.3), nn.Linear(hidden_dim, output_dim) ) def forward(self, x): return self.layers(x) # Train model = SimpleNN(10, 64, 2) optimizer = torch.optim.AdamW(model.parameters(), lr=1e-3) criterion = nn.CrossEntropyLoss() for epoch in range(10): model.train() for batch_x, batch_y in train_loader: optimizer.zero_grad() output = model(batch_x) loss = criterion(output, batch_y) loss.backward() optimizer.step() ``` ## Key Topics ### 1. Neural Network Architectures | Architecture | Use Case | Key Layers | |-------------|----------|------------| | **MLP** | Tabular data | Linear, ReLU, Dropout | | **CNN** | Images | Conv2d, MaxPool2d, BatchNorm | | **RNN/LSTM** | Sequences | LSTM, GRU | | **Transformer** | NLP, Vision | MultiheadAttention | ```python class MLP(nn.Module): def __init__(self, dims, dropout=0.3): supe
- Quick Start
- Key Topics
- 1. Neural Network Architectures
- 2. Training Loop Template
- 3. Learning Rate Scheduling
- 4. Regularization
- 5. Model Checkpointing
- Best Practices
- DO
- DON'T
- Exercises
- Exercise 1: Basic MLP
- Exercise 2: Training with AMP
- Unit Test Template
What does the deep-learning skill do?
Build and train neural networks with PyTorch - MLPs, CNNs, and training best practices
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill deep-learning --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.