Project 8: Binary Classifier Compiler

ML Engineer

Builds on these lessons

Current Task

Objective

.compile() attaches an optimizer and a loss function to a model — required before it can be trained with .fit().

Task: build a Sequential model for binary classification, compile it, and print how many layers it has.

index.py

import tensorflow as tf
from tensorflow.keras import layers, Sequential

model = Sequential([
    layers.Dense(16, activation='relu', input_shape=(10,)),
    layers.Dense(1, activation='sigmoid')
])
model.compile(optimizer='adam', loss='binary_crossentropy')
print(len(model.layers))

* Hint: Correct characters turn green, incorrect ones turn red.

Live Preview

🖼️

Verify your code to see the preview

← Previous Next →