Project 20: Dropout Regularized Model
ML Engineer
Builds on these lessons
Current Task
Objective
Dropout randomly zeroes a fraction of activations during training, another common technique for reducing overfitting.
Task: add a Dropout layer to a small model and print its summary.
index.py
import tensorflow as tf
from tensorflow.keras import layers, Sequential
model = Sequential([
layers.Dense(32, activation='relu', input_shape=(10,)),
layers.Dropout(0.5),
layers.Dense(1)
])
print(model.summary())
* Hint: Correct characters turn green, incorrect ones turn red.
Live Preview
🖼️
Verify your code to see the preview