A Gentle Introduction to Vectors for Machine Learning

Last Updated on August 9, 2019

Vectors are a foundational element of linear algebra.

Vectors are used throughout the field of machine learning in the description of algorithms and processes such as the target variable (y) when training an algorithm.

In this tutorial, you will discover linear algebra vectors for machine learning.

After completing this tutorial, you will know:

• What a vector is and how to define one in Python with NumPy.
• How to perform vector arithmetic such as addition, subtraction, multiplication and division.
• How to perform additional operations such as dot product and multiplication with a scalar.

Kick-start your project with my new book Linear Algebra for Machine Learning, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

A Gentle Introduction to Vectors for Machine Learning
Photo by Lachlan Donald, some rights reserved.

Tutorial Overview

This tutorial is divided into 5 parts; they are:

1. What is a Vector?
2. Defining a Vector
3. Vector Arithmetic
4. Vector Dot Product
5. Vector-Scalar Multiplication