Model Architecture
Learn about neural network architectures and how to design effective models.
Layer Types
Dense Layers
Fully connected layers for learning complex patterns
Convolutional Layers
Extract spatial features from images and signals
Recurrent Layers
Process sequential data with memory
Attention Layers
Focus on relevant parts of input data
Example Architecture
from oneml import Model, layers
model = Model([
layers.Input(shape=(224, 224, 3)),
layers.Conv2D(64, kernel=3, activation="relu"),
layers.MaxPool2D(),
layers.Conv2D(128, kernel=3, activation="relu"),
layers.Flatten(),
layers.Dense(256, activation="relu"),
layers.Dropout(0.5),
layers.Output(10, activation="softmax")
])