In this post, we will dive into the details of TensorFlow Tensors. We will cover all the topics related to Tensors in Tensorflow in these five simple steps:

- **Step I: Definition of Tensors → **What is a Tensor?
- **Step II: Creation of Tensors → **Functions to Create Tensor Objects
- **Step III: Qualifications of Tensors → **Characteristics and Features of Tensor Objects
- **Step IV: Operations with Tensors → **Indexing, Basic Tensor Operations, Shape Manipulation, and Broadcasting
- **Step V: Special Types of Tensors → **Special Tensor Types Other than Regular Tensors

Let’s start!

#### Definition of Tensors: What is a Tensor?

Figure 1. A Visualization of Rank-3 Tensors (Figure by Author)

Tensors are TensorFlow’s multi-dimensional arrays with uniform type. They are very similar to NumPy arrays, and they are immutable, which means that they cannot be altered once created. You can only create a new copy with the edits.

#deep learning #python #tensorflow