Linear Algebra for Data Science — Vectors

Basic vector concepts used in data science and machine learning

Benjamin Obi Tayo Ph.D.

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Benjamin O. Tayo is a data science educator, tutor, coach, mentor, and consultant. Contact me for more information about our services and pricing: benjaminobi@gmail.com

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INTRODUCTION

After going through this article, the reader should learn the following:

  • Definition of Vectors
  • Perform addition and subtraction of vectors
  • Perform scalar multiplication of vectors
  • Use scalar multiplication for feature engineering
  • Define dot product of vectors
  • Use dot products to calculate correlation coefficient

To learn more about the use of matrices in data science and machine learning, see the article below:

Vectors

A vector is a one-dimensional collection of elements. The dimension of a vector n gives number of elements in the vector.

Addition and Subtraction of Vectors

Two vectors having same dimension can be added and subtracted.

Let vectors A and B be given as shown below:

Then the sum of A and B is given as

Scalar Multiplication of Vectors

Let c be a real number, then cA is the vector given by

Feature Engineering Using Scalar Multiplication

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Benjamin Obi Tayo Ph.D.

Dr. Tayo is a data science educator, tutor, coach, mentor, and consultant. Contact me for more information about our services and pricing: benjaminobi@gmail.com