A · BUILDING BLOCKS
Neural Networks
Models made of connected computational units.
Layers
Repeated processing stages inside the network.
02 · Neural Networks & Model Architectures
How Modern Neural Models Are Built
This module explains how neural networks are structured, what layers do, and how major architectures such as CNNs, RNNs, Transformers, Attention-based models, and Diffusion Models fit into the bigger picture.
Learn the building blocks and families of modern neural model architectures.
The Big Picture · architecture family map
Building blocks, families, and mechanisms
NEURAL NETWORKSModels made of connected computational units
↓ LAYERSRepeated processing stages inside the network
COMMON ARCHITECTURE FAMILIES├── CNN · grid-like data such as images
├── RNN / LSTM · sequences processed step by step
└── Transformer · relationships across tokens
├── RNN / LSTM · sequences processed step by step
└── Transformer · relationships across tokens
ATTENTIONA key mechanism used inside Transformers; attention is not the same thing as a Transformer.
DIFFUSION MODELSAnother important generative model family, often used to generate data by reversing a noising process.
Knowledge Structure
Organize the ideas by role
B · ARCHITECTURES
CNN
Often used for grid-like data such as images.
RNN / LSTM
Designed to process sequences step by step.
Transformer
Processes relationships across tokens with attention.
C · MECHANISM
Attention
Helps a model weigh which parts of input matter most.
D · GENERATIVE FAMILY
Diffusion Models
Generate data by learning to reverse a noising process.
Key Distinctions
Related concepts are not interchangeable
Neural NetworkOne type of model structure≠Deep LearningBroader approach that often uses multi-layer networks
AttentionMechanism≠TransformerFull architecture that uses attention
CNNModel architecture≠Computer VisionBroader application area
Diffusion ModelOne model family≠Generative AIBroader capability area
Recommended Learning Path
Learn the structures in order
This is a learning path, not a historical timeline or strict taxonomy.
01Neural Networks
Start with the broad structure.
02Layers
Understand repeated processing blocks.
03CNN and RNN / LSTM
Learn earlier architecture families.
04Transformer
Learn a dominant modern architecture.
05Attention
Understand a key mechanism.
06Diffusion Models
Meet another generative family.
Remember the families
Neural networks are built from layers, different architectures organize those layers in different ways, and attention and diffusion describe important modern modeling ideas.