Project 14: Accuracy Metric Tracker
ML Engineer
Builds on these lessons
Current Task
Objective
A Keras metric like Accuracy accumulates state across update_state() calls, so you can track performance across many batches before reading .result().
Task: update an Accuracy metric with some predictions and print its result.
index.py
import tensorflow as tf
accuracy = tf.keras.metrics.Accuracy()
accuracy.update_state([1, 0, 1, 1], [1, 0, 0, 1])
print(accuracy.result().numpy())
* Hint: Correct characters turn green, incorrect ones turn red.
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