# Sequential Model - Simple and Clean
import tensorflow as tf
from tensorflow import keras
# Define model architecture
model = keras.Sequential([
keras.layers.Dense(128, activation='relu', input_shape=(784,)),
keras.layers.Dropout(0.2),
keras.layers.Dense(64, activation='relu'),
keras.layers.Dropout(0.2),
keras.layers.Dense(10, activation='softmax')
])
# Compile with optimizer, loss, and metrics
model.compile(
optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy']
)
# Model summary
model.summary()