Custom Models and Training with Tensorflow - Custom Models and Training - Part II

1 Custom Models and Training with Tensorflow - Custom Models and Training - Part I

2 Custom Models and Training with Tensorflow - Custom Models and Training - Part II

3 MCQ - Writing a custom training loop will make your code longer, more error-prone, and harder to maintain?

4 MCQ - We can add a scalar value to a tensor?

5 MCQ - The Huber loss is not currently part of the official Keras API, but it is available in tf.keras?

6 MCQ - You cannot create a tensor from a NumPy array?

7 MCQ - You can create a tensor with tf.constant()?

8 MCQ - A TensorFlow tensor is usually a multidimensional array, but it can also hold a scalar?

9 MCQ - TensorFlow Lite runs only on Mac devices?

10 MCQ - TensorFlow's JIT compiler allows it to optimize computations for speed and memory usage?

11 MCQ - TensorFlow has a core similar to Numpy?

12 MCQ - We need lower-level Python API in TensorFlow when extra control is need for writing: