# Linear Algebra (20)

**How to do “Limitless” Math in Python**- Oct 7, 2021.

How to perform arbitrary-precision computation and much more math (and fast too) than what is possible with the built-in math library in Python.**How Machine Learning Leverages Linear Algebra to Solve Data Problems**- Sep 7, 2021.

Why you should learn the fundamentals of linear algebra.**Linear Algebra for Natural Language Processing**- Aug 17, 2021.

Learn about representing word semantics in vector space.**Essential Math for Data Science: Introduction to Systems of Linear Equations**- Aug 6, 2021.

In this post, you’ll see how you can use systems of equations and linear algebra to solve a linear regression problem.**Essential Math for Data Science: Basis and Change of Basis**- May 28, 2021.

In this article, you will learn what the basis of a vector space is, see that any vectors of the space are linear combinations of the basis vectors, and see how to change the basis using change of basis matrices.**KDnuggets™ News 21:n18, May 12: Data Preparation in SQL, with Cheat Sheet!; Rebuilding 7 Python Projects**- May 12, 2021.

Data Preparation in SQL, with Cheat Sheet!; Rebuilding My 7 Python Projects; Applying Python’s Explode Function to Pandas DataFrames; Essential Linear Algebra for Data Science and Machine Learning; Similarity Metrics in NLP**Essential Linear Algebra for Data Science and Machine Learning**- May 10, 2021.

Linear algebra is foundational in data science and machine learning. Beginners starting out along their learning journey in data science--as well as established practitioners--must develop a strong familiarity with the essential concepts in linear algebra.**Essential Math for Data Science: Linear Transformation with Matrices**- Apr 16, 2021.

You’ll start seeing matrices, not only as operations on numbers, but also as a way to transform vector spaces. This conception will give you the foundations needed to understand more complex linear algebra concepts like matrix decomposition.**Essential Math for Data Science: Scalars and Vectors**- Feb 12, 2021.

Linear algebra is the branch of mathematics that studies vector spaces. You’ll see how vectors constitute vector spaces and how linear algebra applies linear transformations to these spaces. You’ll also learn the powerful relationship between sets of linear equations and vector equations.**Essential Math for Data Science: Introduction to Matrices and the Matrix Product**- Feb 5, 2021.

As vectors, matrices are data structures allowing you to organize numbers. They are square or rectangular arrays containing values organized in two dimensions: as rows and columns. You can think of them as a spreadsheet. Learn more here.**Matrix Decomposition Decoded**- Dec 11, 2020.

This article covers matrix decomposition, as well as the underlying concepts of eigenvalues (lambdas) and eigenvectors, as well as discusses the purpose behind using matrix and vectors in linear algebra.**KDnuggets™ News 20:n29, Jul 29: Easy Guide To Data Preprocessing In Python; Building a better Spark UI; Computational Algebra for Coders: The Free Course**- Jul 29, 2020.

An easy guide to data pre-processing in Python; Monitoring Apache Spark with a better Spark UI; Computational Linear Algebra for Coders: the free course; Labelling data with Snorkel; Bayesian Statistics.**Computational Linear Algebra for Coders: The Free Course**- Jul 27, 2020.

Interested in learning more about computational linear algebra? Check out this free course from fast.ai, structured with a top-down teaching method, and solidify your understanding of an important set of machine learning-related concepts.**4 Free Math Courses to do and Level up your Data Science Skills**- Jun 22, 2020.

Just as there is no Data Science without data, there's no science in data without mathematics. Strengthening your foundational skills in math will level you up as a data scientist that will enable you to perform with greater expertise.**Top KDnuggets tweets, May 13-19: Linear algebra and optimization and machine learning: A textbook**- May 21, 2020.

Also: Everything you need to become a self-taught #MachineLearning Engineer ; SQL Cheat Sheet (2020) - a useful cheat sheet that documents some of the more commonly used elements of SQL;**Linear algebra and optimization and machine learning: A textbook**- May 18, 2020.

This book teaches linear algebra and optimization as the primary topics of interest, and solutions to machine learning problems as applications of these methods. Therefore, the book also provides significant exposure to machine learning.**A Top Machine Learning Algorithm Explained: Support Vector Machines (SVM)**- Mar 18, 2020.

Support Vector Machines (SVMs) are powerful for solving regression and classification problems. You should have this approach in your machine learning arsenal, and this article provides all the mathematics you need to know -- it's not as hard you might think.**10 Free Must-See Courses for Machine Learning and Data Science**- Nov 8, 2018.

Check out a collection of free machine learning and data science courses to kick off your winter learning season.**New Book: Linear Algebra – what you need for Machine Learning and Data Science now**- Oct 24, 2018.

From machine learning and data science to engineering and finance, linear algebra is an important prerequisite for the careers of today and of the future. Learn the math you need with this book.**Boost your data science skills. Learn linear algebra.**- May 3, 2018.

The aim of these notebooks is to help beginners/advanced beginners to grasp linear algebra concepts underlying deep learning and machine learning. Acquiring these skills can boost your ability to understand and apply various data science algorithms.