Basic Data Structures

Here, we’ll discuss some concepts that will help us to understand certain details provided in the course. First, we’ll discuss several mathematical data structures found throughout the course, followed by a description of the various operations performed on those data structures. After that, we’ll discuss the concept of probabilities. Probabilities play a vital role in machine learning because they usually give insights into how uncertain a model is about its prediction. Finally, we’ll conclude this appendix with a guide on how to use TensorBoard as a visualization tool for word embeddings.

Next, we’ll look at some basic data structures.

Scalar

A scalar is a single number, unlike a matrix or a vector. For example, 1.3 is a scalar. A scalar can be mathematically denoted as follows: $n \in R.$

Here,  $R$ is the real number space.

Vectors

A vector is an array of numbers. Unlike a set where there’s no order to the elements, a vector has a certain order to the elements. An example vector is $[1.0, 2.0, 1.4, 2.3].$ Mathematically,