Archive | Linear Algebra

10 Examples of Linear Algebra in Machine Learning

10 Examples of Linear Algebra in Machine Learning

Linear algebra is a sub-field of mathematics concerned with vectors, matrices, and linear transforms. It is a key foundation to the field of machine learning, from notations used to describe the operation of algorithms to the implementation of algorithms in code. Although linear algebra is integral to the field of machine learning, the tight relationship […]

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No Bullshit Guide To Linear Algebra

No Bullshit Guide To Linear Algebra Review

There are many books that provide an introduction to the field of linear algebra. Most are textbooks targeted at undergraduate students and are full of theoretical digressions that are barely relevant and mostly distracting to a beginner or practitioner to the field. In this post, you will discover the book “No bullshit guide to linear […]

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How to Calculate the Principal Component Analysis from Scratch in Python

How to Calculate Principal Component Analysis (PCA) from Scratch in Python

An important machine learning method for dimensionality reduction is called Principal Component Analysis. It is a method that uses simple matrix operations from linear algebra and statistics to calculate a projection of the original data into the same number or fewer dimensions. In this tutorial, you will discover the Principal Component Analysis machine learning method […]

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A Gentle Introduction to Expected Value, Variance, and Covariance with NumPy

A Gentle Introduction to Expected Value, Variance, and Covariance with NumPy

Fundamental statistics are useful tools in applied machine learning for a better understanding your data. They are also the tools that provide the foundation for more advanced linear algebra operations and machine learning methods, such as the covariance matrix and principal component analysis respectively. As such, it is important to have a strong grip on […]

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A Gentle Introduction to Singular-Value Decomposition

How to Calculate the SVD from Scratch with Python

Matrix decomposition, also known as matrix factorization, involves describing a given matrix using its constituent elements. Perhaps the most known and widely used matrix decomposition method is the Singular-Value Decomposition, or SVD. All matrices have an SVD, which makes it more stable than other methods, such as the eigendecomposition. As such, it is often used […]

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Linear Algebra Cheat Sheet for Machine Learning

Linear Algebra Cheat Sheet for Machine Learning

All of the Linear Algebra Operations that You Need to Use in NumPy for Machine Learning. The Python numerical computation library called NumPy provides many linear algebra functions that may be useful as a machine learning practitioner. In this tutorial, you will discover the key functions for working with vectors and matrices that you may […]

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