As much as I had learned a lot from the MLS courses up until this date, today I found myself totally lost on the concept of matrix/array *dimension*, although I kept revisiting the Data in TensorFlow and Building a Neural Network video modules a few times.

Before attending this course and just by reading internet articles about NumPy, my understanding was: when we define an array (x, y), x automatically explains the dimension of our array. In other words, in the so-called “ND Array,” N always represents x (which is meanwhile driven by the number of rows).

However, at some point in the aforementioned videos, in one instance the respected instructor called a 1x1 matrix a 2D array. In another slide I was confused by a 4x2 matrix introduced again as a 2D array.

My questions:

- Is array in NumPy the same concept as matrix in TensorFlow, in terms of
*dimentionality*? - If the two concepts are different, how should we differentiate them exactly?

I would appreciate any explication from my fellow classmates reading my post online.

Thanks