Introduction and setup of TensorFlow

TensorFlow (TF) has in its name the word Tensor, which is a synonym of vector. TF, thus, is a Python framework that is designed to excel at vectorial operations pertaining to the modeling of neural networks. It is the most popular library for machine learning.

As data scientists, we have a preference towards TF because it is free, opensource with a strong user base, and it uses state-of-the-art research on the graph-based execution of tensor operations.

Setup

Let us now begin with instructions to set up or verify that you have the proper setup:

1. To begin the installation of TF, run the following command in your Colaboratory:

%tensorflow_version 2.x
!pip install tensorflow

This will install about 20 libraries that are required to run TF, including numpy, for example.

Notice the exclamation mark (!) at the beginning of the command? This is how you will run shell commands on Colaboratory. For example, say that you want to remove a file named model.h5...