Project 25: TensorBoard Logger Setup
ML Engineer
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Current Task
Objective
The TensorBoard callback logs training metrics to a directory that TensorBoard's UI can visualize — the standard way to monitor training progress.
Task: create a TensorBoard callback pointing at a logs directory and print that directory.
index.py
import tensorflow as tf
tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir='./logs')
print(tensorboard_callback.log_dir)
* Hint: Correct characters turn green, incorrect ones turn red.
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