Predictive Analytics with TensorFlow 3.3: TensorFlow Programming Model

The video tutorial introduces the TensorFlow programming model, which is divided into four phases: constructing the computational graph, creating a session, running the session, and data collection. It demonstrates setting up a TensorFlow notebook, importing necessary libraries, and provides an example of multiplying two numbers using TensorFlow. The tutorial explains the use of placeholders for efficient data exchange and details the process of building and executing a computational model. The video concludes with a preview of the next topic on data models in TensorFlow.

What is the significance of the computational graph in TensorFlow?

How does TensorFlow improve the efficiency of operations like multiplication?