Neural Network Design

SKILL.md

Neural Network Design

Overview

This skill covers designing and implementing neural network architectures including CNNs, RNNs, Transformers, and ResNets using PyTorch and TensorFlow, with focus on architecture selection, layer composition, and optimization techniques.

When to Use

Designing custom neural network architectures for computer vision tasks like image classification or object detection

Building sequence models for time series forecasting, natural language processing, or video analysis

Implementing transformer-based models for language understanding or generation tasks

Creating hybrid architectures that combine CNNs, RNNs, and attention mechanisms

Optimizing network depth, width, and skip connections for better training and performance

Selecting appropriate activation functions, normalization layers, and regularization techniques

Core Architecture Types